Essec\Faculty\Model\Profile {#2209
#_id: "B00683004"
#_source: array:39 [
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"academId" => "2061"
"slug" => "ljubic-ivana"
"fullName" => "Ivana LJUBIC"
"lastName" => "LJUBIC"
"firstName" => "Ivana"
"title" => array:2 [
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"en" => "Professor"
]
"email" => "ljubic@essec.edu"
"status" => "ACTIF"
"campus" => "Campus de Cergy"
"departments" => []
"phone" => "+33 (0)1 34 43 97 26"
"sites" => []
"facNumber" => "2061"
"externalCvUrl" => "https://faculty.essec.edu/cv/ljubic-ivana/pdf"
"googleScholarUrl" => "https://scholar.google.com/citations?user=o1Ym0_AAAAAJ"
"facOrcId" => "https://orcid.org/0000-0002-4834-6284"
"career" => array:14 [
0 => Essec\Faculty\Model\CareerItem {#2291
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"endDate" => "2021-08-31"
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]
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"en" => "Academic Director of the ESSEC & Mannheim EMBA program"
]
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"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
1 => Essec\Faculty\Model\CareerItem {#2292
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]
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]
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"en" => "Université de Vienne"
]
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"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
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"en" => "TU Wien"
]
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"en" => "Austria"
]
]
+lang: "fr"
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}
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]
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4 => Essec\Faculty\Model\CareerItem {#2295
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]
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5 => Essec\Faculty\Model\CareerItem {#2296
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]
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}
6 => Essec\Faculty\Model\CareerItem {#2297
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"fr" => "Université de Vienne"
"en" => "Université de Vienne"
]
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"fr" => "Autriche"
"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
7 => Essec\Faculty\Model\CareerItem {#2298
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"en" => "Universidad Adolfo Ibáñez"
]
"country" => array:2 [
"fr" => "Chili"
"en" => "Chile"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
8 => Essec\Faculty\Model\CareerItem {#2299
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"en" => "Université Paris-Dauphine, PSL"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
9 => Essec\Faculty\Model\CareerItem {#2300
#_index: null
#_id: null
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]
"institution" => array:2 [
"fr" => "Technische Universität Berlin"
"en" => "Technische Universität Berlin"
]
"country" => array:2 [
"fr" => "Allemagne"
"en" => "Germany"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
10 => Essec\Faculty\Model\CareerItem {#2301
#_index: null
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"institution" => array:2 [
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"en" => "TU Dortmund Universität"
]
"country" => array:2 [
"fr" => "Allemagne"
"en" => "Germany"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
11 => Essec\Faculty\Model\CareerItem {#2302
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]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
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}
12 => Essec\Faculty\Model\CareerItem {#2303
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}
13 => Essec\Faculty\Model\CareerItem {#2304
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]
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}
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0 => Essec\Faculty\Model\Diplome {#2211
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1 => Essec\Faculty\Model\Diplome {#2213
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"label" => array:2 [
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"en" => "Université de Vienne"
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}
2 => Essec\Faculty\Model\Diplome {#2210
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"en" => "University of Belgrade"
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]
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"bio" => array:2 [
"fr" => """
<p><b><a href="https://orcid.org/0000-0002-4834-6284">ORCID Ivana Ljubic</a></b></p>\n
\n
<p><a href="http://scholar.google.com/citations?user=o1Ym0_AAAAAJ&hl=en" target="_blank"><b>Google Scholar Profile</b></a> </p>\n
\n
<p><b><a href="https://ivanaljubic.github.io/">Personal web-site</a></b></p>\n
\n
<p>See the <b><a href="https://ivanaljubic.github.io/publications/">full publication list</a> </b>including preprints and a list of <a href="https://ivanaljubic.github.io/talks/"><b>scientific </b></a><a href="https://ivanaljubic.github.io/talks/"><b>talks</b></a>.</p>\n
\n
<p><b>NEWS:</b></p>\n
\n
<ul>\n
\t<li><b><a href="https://onlinelibrary.wiley.com/page/journal/10970037/homepage/glover-klingman_prize.htm">The Glover-Klingman Prize</a> </b>for the best <a href="https://onlinelibrary.wiley.com/journal/10970037">Networks</a> paper in 2021 for the article Ivana Ljubić: <a class="issue-item__title visitable" href="https://onlinelibrary.wiley.com/doi/10.1002/net.22005" title="Solving Steiner trees: Recent advances, challenges, and perspectives">Solving Steiner trees: Recent advances, challenges, and perspectives</a>, Networks 77 (2): 177-204, 2021</li>\n
\t<li><a href="https://www.sciencedirect.com/science/article/pii/S2192440622000028" target="_blank"><b>Marguerite Frank Award</b></a> for the best EJCO paper in 2021 for the paper <a href="https://www.sciencedirect.com/science/article/pii/S2192440621001349" target="_blank"><b>A Survey on Mixed-Integer Programming Techniques in Bilevel Optimization</b></a>. Jointly with Thomas Kleinert, Martine Labbé, and Martin Schmidt.</li>\n
\t<li>Keynote speaker: <a href="https://sites.google.com/view/cpaior2023/keynote-speakers">CPAIOR 2023</a> </li>\n
\t<li>Plenary speaker: <a href="https://www.fondation-hadamard.fr/fr/la-fmjh-soutient/recherche/home/pgmo-days/">PGMO Days 2022</a>, Nov 2022</li>\n
\t<li>Plenary speaker: <a href="https://www.siam.org/conferences/cm/program/invited-presentations/op21-invited-presentations">SIAM Conference on Optimization</a> (OP21), July 2021 </li>\n
</ul>\n
\n
<p><b>BIO:</b></p>\n
\n
<p>Ivana Ljubic is Full Professor in Operations Research at ESSEC. She teaches Decision Analysis, Optimal Decision Making, Operations Research (OR) and Business Mathematics in ESSEC MSc, PhD and Advanced Master programs. Prior to joining ESSEC in 2015, she was appointed at the University of Vienna. She also worked as Visiting Scholar/Professor at the Robert H. Smith School of Business at the University of Maryland, TU Dortmund, TU Berlin, Dauphine University, etc. From 2017 to 2019 she was Academic Director of the ESSEC EMBA program, and from 2017 to 2021 she was Academic Director of the <a href="http://executive-education.essec.edu/en/program/embas-en/essec-mannheim-emba-modular-track/" target="_blank">ESSEC & Mannheim EMBA</a> program. She has published numerous scientific articles in leading outlets and has been ranked since 2018 amongst the Top 5% of most successful business professors in Germany, Switzerland, and Austria according to <a href="https://www.forschungsmonitoring.org/ranking/bwl/authors">various publication rankings</a>. </p>\n
\n
<p>Ivana Ljubic has carried out consulting studies and industrial contracts for leading telecommunication providers in France and Austria. After completing her PhD in computer science, she also worked for 2 years as Financial Analyst for a Siemens spin-off (fin4cast), focusing on portfolio optimization.</p>\n
\n
<p>Research interests of Ivana Ljubic include combinatorial optimization, optimization under uncertainty, bilevel optimization. She uses tools and methods of mixed integer (non-) linear programming, meta-heuristics and their successful combinations for solving optimization problems with applications in network design, telecommunications, transportation, logistics, routing and bioinformatics. She has published more than 70 articles in leading OR journals, including Operations Research, Management Science, Mathematical Programming, INFORMS JOC, European Journal of Operational Research.</p>\n
\n
<p>She is member of the Editorial Advisory Board for the journals European Journal of Operational Research, Computers & Operations Research, and she is Associate Editor for the journals Operations Research (since 2023), Transportation Science (since 2021), Networks (since 2020), Journal of Global Optimization (2019-2021) and Omega (2016-2020). She also served as guest-editor of journals: Discrete Applied Mathematics, European Journal of Operational Research and Annals of Operations Research.</p>\n
\n
<p>She is co-leading the axis "<a href="http://gdrro.lip6.fr/?q=node/232">Combinatorial Optimization and Integer Programming</a>" of <a href="http://gdrro.lip6.fr/">GDR RO</a> and its working group "<a href="http://gdrro.lip6.fr/?q=node/35">Polyhedra and Combinatorial Optimization</a>" (POC). She is past chair of the <a href="http://INFORMS Telecommunication and Network Analytics">INFORMS Telecommunication and Network Analytics </a>Section. From 2010-2016 she was member of council of the INFORMS Telecommunication Section and from 2006 to 2008 she was member of the executive board of the Austrian OR Society (<a href="https://oegor.wordpress.com/">OEGOR</a>).</p>\n
\n
<p>She has received numerous research grants, including those from the CY Initiative of Excellence, French Ministry of Foreign Affairs (PHC program), Austrian Academy of Sciences (OEAW), Austrian Research Fund (FWF) and European Commission (ERA-NET).</p>\n
\n
<p><b>SOME VIDEO LECTURES:</b></p>\n
\n
<ul>\n
\t<li>Beale Lecture 2021 - panel discussion honoring <a href="https://www.lse.ac.uk/management/people/emeriti-visiting-staff/aland">Dr. Ailsa Land</a><b>, </b>the winner of Beale Medal 2019 (<a href="https://youtu.be/jBQCOSKL1ho?t=1780">video</a>)</li>\n
\t<li>Plenary talk: <a href="https://homepage.univie.ac.at/ivana.ljubic/presentations1.html">New integer and Bilevel Formulations for the k-Vertex Cut Problem</a>,<br />\n
\t<a href="http://opslab.dieti.unina.it/index.php/en/laboratory?id=59">5th AIRO Young Workshop</a>, Napoli, Italy and online, February 12, 2021 (<a href="https://www.youtube.com/watch?v=LXjE8PWxaPQ&feature=youtu.be">Video Lecture</a>)</li>\n
\t<li>Plenary talk: <a href="https://">Casting Light on the Hidden Bilevel Structure of the Capacitated Vertex Separator Problem</a>, Mixed Integer Programming Workshop 2020 Online Edition (MIP2020), May 18, 2020 (<a href="https://www.youtube.com/watch?v=dl9KW0CnQ74">Video</a>)</li>\n
\t<li>Invited Lecture: <a href="https://alop.uni-trier.de/wp-content/uploads/2020/10/ALOP_Ljubic.pdf">Branch-and-Cut Solvers for Mixed-Integer Bilevel Linear Programs</a>,<br />\n
\t<a href="https://alop.uni-trier.de/event/autumn-school-on-bilevel-optimization/">Autumn School on Bilevel Optimization</a> (online), Oct 12-14, 2020, Uni Trier, Germany (Video Lecture <a href="https://www.youtube.com/watch?v=NNdY5vf80AM">Part 1</a> and <a href="https://www.youtube.com/watch?v=x1t4z7aCVEY">Part 2</a>)</li>\n
</ul>\n
"""
"en" => """
<p> </p>\n
\n
<p><b><a href="https://orcid.org/0000-0002-4834-6284">ORCID Ivana Ljubic</a></b></p>\n
\n
<p><a href="http://scholar.google.com/citations?user=o1Ym0_AAAAAJ&hl=en" target="_blank"><b>Google Scholar Profile</b></a> </p>\n
\n
<p><b><a href="https://ivanaljubic.github.io/">Personal web-site</a></b></p>\n
\n
<p>See the <b><a href="https://ivanaljubic.github.io/publications/">full publication list</a> </b>including preprints and a list of <a href="https://ivanaljubic.github.io/talks/"><b>scientific </b></a><a href="https://ivanaljubic.github.io/talks/"><b>talks</b></a>.</p>\n
\n
<p><b>NEWS:</b></p>\n
\n
<ul>\n
\t<li><b><a href="https://onlinelibrary.wiley.com/page/journal/10970037/homepage/glover-klingman_prize.htm">The Glover-Klingman Prize</a> </b>for the best <a href="https://onlinelibrary.wiley.com/journal/10970037">Networks</a> paper in 2021 for the article Ivana Ljubić: <a class="issue-item__title visitable" href="https://onlinelibrary.wiley.com/doi/10.1002/net.22005" title="Solving Steiner trees: Recent advances, challenges, and perspectives">Solving Steiner trees: Recent advances, challenges, and perspectives</a>, Networks 77 (2): 177-204, 2021</li>\n
\t<li><a href="https://www.sciencedirect.com/science/article/pii/S2192440622000028" target="_blank"><b>Marguerite Frank Award</b></a> for the best EJCO paper in 2021 for the paper <a href="https://www.sciencedirect.com/science/article/pii/S2192440621001349" target="_blank"><b>A Survey on Mixed-Integer Programming Techniques in Bilevel Optimization</b></a>. Jointly with Thomas Kleinert, Martine Labbé, and Martin Schmidt.</li>\n
\t<li>Keynote speaker: <a href="https://sites.google.com/view/cpaior2023/keynote-speakers">CPAIOR 2023</a> </li>\n
\t<li>Plenary speaker: <a href="https://www.fondation-hadamard.fr/fr/la-fmjh-soutient/recherche/home/pgmo-days/">PGMO Days 2022</a>, Nov 2022</li>\n
\t<li>Plenary speaker: <a href="https://www.siam.org/conferences/cm/program/invited-presentations/op21-invited-presentations">SIAM Conference on Optimization</a> (OP21), July 2021 </li>\n
</ul>\n
\n
<p><b>BIO:</b></p>\n
\n
<p>Ivana Ljubic is Full Professor in Operations Research at ESSEC. She teaches Decision Analysis, Optimal Decision Making, Operations Research (OR) and Business Mathematics in ESSEC MSc, PhD and Advanced Master programs. Prior to joining ESSEC in 2015, she was appointed at the University of Vienna. She also worked as Visiting Scholar/Professor at the Robert H. Smith School of Business at the University of Maryland, TU Dortmund, TU Berlin, Dauphine University, etc. From 2017 to 2019 she was Academic Director of the ESSEC EMBA program, and from 2017 to 2021 she was Academic Director of the <a href="http://executive-education.essec.edu/en/program/embas-en/essec-mannheim-emba-modular-track/" target="_blank">ESSEC & Mannheim EMBA</a> program. She has published numerous scientific articles in leading outlets and has been ranked since 2018 amongst the Top 5% of most successful business professors in Germany, Switzerland, and Austria according to <a href="https://www.forschungsmonitoring.org/ranking/bwl/authors">various publication rankings</a>. </p>\n
\n
<p>Ivana Ljubic has carried out consulting studies and industrial contracts for leading telecommunication providers in France and Austria. After completing her PhD in computer science, she also worked for 2 years as Financial Analyst for a Siemens spin-off (fin4cast), focusing on portfolio optimization.</p>\n
\n
<p>Research interests of Ivana Ljubic include combinatorial optimization, optimization under uncertainty, bilevel optimization. She uses tools and methods of mixed integer (non-) linear programming, meta-heuristics and their successful combinations for solving optimization problems with applications in network design, telecommunications, transportation, logistics, routing and bioinformatics. She has published more than 70 articles in leading OR journals, including Operations Research, Management Science, Mathematical Programming, INFORMS JOC, European Journal of Operational Research.</p>\n
\n
<p>She is member of the Editorial Advisory Board for the journals European Journal of Operational Research, Computers & Operations Research, and she is Associate Editor for the journals Operations Research (since 2023), Transportation Science (since 2021), Networks (since 2020), Journal of Global Optimization (2019-2021) and Omega (2016-2020). She also served as guest-editor of journals: Discrete Applied Mathematics, European Journal of Operational Research and Annals of Operations Research.</p>\n
\n
<p>She is co-leading the axis "<a href="http://gdrro.lip6.fr/?q=node/232">Combinatorial Optimization and Integer Programming</a>" of <a href="http://gdrro.lip6.fr/">GDR RO</a> and its working group "<a href="http://gdrro.lip6.fr/?q=node/35">Polyhedra and Combinatorial Optimization</a>" (POC). She is past chair of the <a href="http://INFORMS Telecommunication and Network Analytics">INFORMS Telecommunication and Network Analytics </a>Section. From 2010-2016 she was member of council of the INFORMS Telecommunication Section and from 2006 to 2008 she was member of the executive board of the Austrian OR Society (<a href="https://oegor.wordpress.com/">OEGOR</a>).</p>\n
\n
<p>She has received numerous research grants, including those from the CY Initiative of Excellence, French Ministry of Foreign Affairs (PHC program), Austrian Academy of Sciences (OEAW), Austrian Research Fund (FWF) and European Commission (ERA-NET).</p>\n
\n
<p><b>SOME VIDEO LECTURES:</b></p>\n
\n
<ul>\n
\t<li>Beale Lecture 2021 - panel discussion honoring <a href="https://www.lse.ac.uk/management/people/emeriti-visiting-staff/aland">Dr. Ailsa Land</a><b>, </b>the winner of Beale Medal 2019 (<a href="https://youtu.be/jBQCOSKL1ho?t=1780">video</a>)</li>\n
\t<li>Plenary talk: <a href="https://homepage.univie.ac.at/ivana.ljubic/presentations1.html">New integer and Bilevel Formulations for the k-Vertex Cut Problem</a>,<br />\n
\t<a href="http://opslab.dieti.unina.it/index.php/en/laboratory?id=59">5th AIRO Young Workshop</a>, Napoli, Italy and online, February 12, 2021 (<a href="https://www.youtube.com/watch?v=LXjE8PWxaPQ&feature=youtu.be">Video Lecture</a>)</li>\n
\t<li>Plenary talk: <a href="https://">Casting Light on the Hidden Bilevel Structure of the Capacitated Vertex Separator Problem</a>, Mixed Integer Programming Workshop 2020 Online Edition (MIP2020), May 18, 2020 (<a href="https://www.youtube.com/watch?v=dl9KW0CnQ74">Video</a>)</li>\n
\t<li>Invited Lecture: <a href="https://alop.uni-trier.de/wp-content/uploads/2020/10/ALOP_Ljubic.pdf">Branch-and-Cut Solvers for Mixed-Integer Bilevel Linear Programs</a>,<br />\n
\t<a href="https://alop.uni-trier.de/event/autumn-school-on-bilevel-optimization/">Autumn School on Bilevel Optimization</a> (online), Oct 12-14, 2020, Uni Trier, Germany (Video Lecture <a href="https://www.youtube.com/watch?v=NNdY5vf80AM">Part 1</a> and <a href="https://www.youtube.com/watch?v=x1t4z7aCVEY">Part 2</a>)</li>\n
</ul>\n
"""
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"en" => "Université Paris-Dauphine, PSL"
]
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"fr" => "France"
"en" => "France"
]
]
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}
3 => Essec\Faculty\Model\TeachingItem {#2288
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"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
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]
]
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}
4 => Essec\Faculty\Model\TeachingItem {#2282
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"en" => "Université de Vienne"
]
"country" => array:2 [
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"en" => "Austria"
]
]
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}
5 => Essec\Faculty\Model\TeachingItem {#2283
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"en" => "Université de Vienne"
]
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]
]
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}
6 => Essec\Faculty\Model\TeachingItem {#2289
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"en" => "Université de Vienne"
]
"country" => array:2 [
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]
]
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}
7 => Essec\Faculty\Model\TeachingItem {#2284
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"en" => "University of Bologna"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
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}
8 => Essec\Faculty\Model\TeachingItem {#2285
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]
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]
]
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}
9 => Essec\Faculty\Model\TeachingItem {#2286
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]
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]
]
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}
10 => Essec\Faculty\Model\TeachingItem {#2287
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]
]
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}
11 => Essec\Faculty\Model\TeachingItem {#2290
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]
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}
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}
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}
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}
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}
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}
7 => Essec\Faculty\Model\ExtraActivity {#2219
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}
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}
9 => Essec\Faculty\Model\ExtraActivity {#2221
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}
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}
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+"parent": Essec\Faculty\Model\Profile {#2209}
}
]
"theses" => array:12 [
0 => Essec\Faculty\Model\These {#2326
#_index: null
#_id: null
#_source: array:9 [
"year" => "2014"
"startDate" => null
"endDate" => "2014"
"student" => "ALVAREZ-MIRANDA E."
"firstJob" => ""
"label" => array:2 [
"fr" => "Eduardo Álvarez-Miranda, University of Bologna (co-supervisé avec P. Toth)"
"en" => "Eduardo Álvarez-Miranda, University of Bologna (co-supervised with P. Toth)"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "University of Bologna"
"en" => "University of Bologna"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
1 => Essec\Faculty\Model\These {#2327
#_index: null
#_id: null
#_source: array:9 [
"year" => null
"startDate" => null
"endDate" => null
"student" => "BRANDSTÄTTER G."
"firstJob" => ""
"label" => array:2 [
"fr" => "Georg Brandstätter, University of Vienna (avec M. Leitner)"
"en" => "Georg Brandstätter, University of Vienna (with M. Leitner)"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "Université de Vienne"
"en" => "Université de Vienne"
]
"country" => array:2 [
"fr" => "Autriche"
"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
2 => Essec\Faculty\Model\These {#2328
#_index: null
#_id: null
#_source: array:9 [
"year" => "2013"
"startDate" => null
"endDate" => "2013"
"student" => "BÜSING C."
"firstJob" => ""
"label" => array:2 [
"fr" => "Christina Büsing, Univ. of Vienna (now at RWTH Aachen)"
"en" => "Christina Büsing, Univ. of Vienna (now at RWTH Aachen)"
]
"role" => array:2 [
"fr" => "Directeur de thèse"
"en" => "Thesis director"
]
"institution" => array:2 [
"fr" => "Université de Vienne"
"en" => "Université de Vienne"
]
"country" => array:2 [
"fr" => "Autriche"
"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
3 => Essec\Faculty\Model\These {#2329
#_index: null
#_id: null
#_source: array:9 [
"year" => "2019"
"startDate" => null
"endDate" => "2019"
"student" => "DE MELO DA SILVA M."
"firstJob" => ""
"label" => array:2 [
"fr" => "Marcos de Melo da Silva, ESSEC"
"en" => "Marcos de Melo da Silva, ESSEC"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
4 => Essec\Faculty\Model\These {#2330
#_index: null
#_id: null
#_source: array:9 [
"year" => "2013"
"startDate" => null
"endDate" => "2013"
"student" => "GOLLOWITZER S."
"firstJob" => ""
"label" => array:2 [
"fr" => "Stefan Gollowitzer (OEGOR Dissertation Award 2013), University of Vienna (avec I. Bomze)"
"en" => "Stefan Gollowitzer (OEGOR Dissertation Award 2013), University of Vienna (with I. Bomze)"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "Université de Vienne"
"en" => "Université de Vienne"
]
"country" => array:2 [
"fr" => "Autriche"
"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
5 => Essec\Faculty\Model\These {#2331
#_index: null
#_id: null
#_source: array:9 [
"year" => null
"startDate" => null
"endDate" => null
"student" => "HASSANZADEH A."
"firstJob" => ""
"label" => array:2 [
"fr" => "Alborz Hassanzadeh, ESSEC (avec L. Alfandari)"
"en" => "Alborz Hassanzadeh, ESSEC (with L. Alfandari)"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
6 => Essec\Faculty\Model\These {#2332
#_index: null
#_id: null
#_source: array:9 [
"year" => "2015"
"startDate" => null
"endDate" => "2015"
"student" => "LEITNER M."
"firstJob" => ""
"label" => array:2 [
"fr" => "Markus Leitner, Univ. of Vienna (désormais à Vrije Universiteit Amsterdam)"
"en" => "Markus Leitner, Univ. of Vienna (now at Vrije Universiteit Amsterdam)"
]
"role" => array:2 [
"fr" => "Directeur de thèse"
"en" => "Thesis director"
]
"institution" => array:2 [
"fr" => "Université de Vienne"
"en" => "Université de Vienne"
]
"country" => array:2 [
"fr" => "Autriche"
"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
7 => Essec\Faculty\Model\These {#2333
#_index: null
#_id: null
#_source: array:9 [
"year" => "2017"
"startDate" => null
"endDate" => "2017"
"student" => "LUIPERSBECK M."
"firstJob" => ""
"label" => array:2 [
"fr" => "Martin Luipersbeck, University of Vienna (Finalist for the EURO Doctoral Dissertation Award 2018) (avec M. Leitner)"
"en" => "Martin Luipersbeck, University of Vienna (Finalist for the EURO Doctoral Dissertation Award 2018) (with M. Leitner)"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "Université de Vienne"
"en" => "Université de Vienne"
]
"country" => array:2 [
"fr" => "Autriche"
"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
8 => Essec\Faculty\Model\These {#2334
#_index: null
#_id: null
#_source: array:9 [
"year" => null
"startDate" => null
"endDate" => null
"student" => "MOUACI A."
"firstJob" => ""
"label" => array:2 [
"fr" => "Ahlam Mouaci, University Paris Dauphine"
"en" => "Ahlam Mouaci, University Paris Dauphine"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "Université Paris-Dauphine, PSL"
"en" => "Université Paris-Dauphine, PSL"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
9 => Essec\Faculty\Model\These {#2335
#_index: null
#_id: null
#_source: array:9 [
"year" => "2013"
"startDate" => null
"endDate" => "2013"
"student" => "PUTZ P."
"firstJob" => ""
"label" => array:2 [
"fr" => "Peter Putz, University of Vienna (avec I. Bomze)"
"en" => "Peter Putz, University of Vienna (with I. Bomze)"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "Université de Vienne"
"en" => "Université de Vienne"
]
"country" => array:2 [
"fr" => "Autriche"
"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
10 => Essec\Faculty\Model\These {#2336
#_index: null
#_id: null
#_source: array:9 [
"year" => "2015"
"startDate" => null
"endDate" => "2015"
"student" => "SINNL M."
"firstJob" => ""
"label" => array:2 [
"fr" => "Markus Sinnl, University of Vienna (OEGOR Dissertation Award 2016 and INFORMS SOLA Dissertation Award 2016) (avec I. Bomze)"
"en" => "Markus Sinnl, University of Vienna (OEGOR Dissertation Award 2016 and INFORMS SOLA Dissertation Award 2016) (with I. Bomze)"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "Université de Vienne"
"en" => "Université de Vienne"
]
"country" => array:2 [
"fr" => "Autriche"
"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
11 => Essec\Faculty\Model\These {#2337
#_index: null
#_id: null
#_source: array:9 [
"year" => "2013"
"startDate" => null
"endDate" => "2013"
"student" => "WASSERMANN B."
"firstJob" => ""
"label" => array:2 [
"fr" => "Bertram Wassermann, University of Vienna (avec I. Bomze)"
"en" => "Bertram Wassermann, University of Vienna (with I. Bomze)"
]
"role" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
"institution" => array:2 [
"fr" => "Université de Vienne"
"en" => "Université de Vienne"
]
"country" => array:2 [
"fr" => "Autriche"
"en" => "Austria"
]
]
+lang: "fr"
+"parent": Essec\Faculty\Model\Profile {#2209}
}
]
"indexedAt" => "2024-07-15T10:21:27.000Z"
"contributions" => array:205 [
0 => Essec\Faculty\Model\Contribution {#2339
#_index: "academ_contributions"
#_id: "2133"
#_source: array:18 [
"id" => "2133"
"slug" => "on-the-use-of-intersection-cuts-for-bilevel-optimization"
"yearMonth" => "2018-11"
"year" => "2018"
"title" => "On the Use of Intersection Cuts for Bilevel Optimization"
"description" => "FISCHETTI, M., LJUBIC, I., MONACI, M. et SINNL, M. (2018). On the Use of Intersection Cuts for Bilevel Optimization. <i>Mathematical Programming</i>, 172(1-2), pp. 77-103."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "FISCHETTI M."
]
2 => array:1 [
"name" => "MONACI M."
]
3 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://link.springer.com/article/10.1007/s10107-017-1189-5"
"publicationInfo" => array:3 [
"pages" => "77-103"
"volume" => "172"
"number" => "1-2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We address a generic mixed-integer bilevel linear program (MIBLP), i.e., a bilevel optimization problem where all objective functions and constraints are linear, and some/all variables are required to take integer values. We first propose necessary modifications needed to turn a standard branch-and-bound MILP solver into an exact and finitely-convergent MIBLP solver, also addressing MIBLP unboundedness and infeasibility. As in other approaches from the literature, our scheme is finitely-convergent in case both the leader and the follower problems are pure integer. In addition, it is capable of dealing with continuous variables both in the leader and in follower problems—provided that the leader variables influencing follower’s decisions are integer and bounded. We then introduce new classes of linear inequalities to be embedded in this branch-and-bound framework, some of which are intersection cuts based on feasible-free convex sets. We present a computational study on various classes of benchmark instances available from the literature, in which we demonstrate that our approach outperforms alternative state-of-the-art MIBLP methods."
"en" => "We address a generic mixed-integer bilevel linear program (MIBLP), i.e., a bilevel optimization problem where all objective functions and constraints are linear, and some/all variables are required to take integer values. We first propose necessary modifications needed to turn a standard branch-and-bound MILP solver into an exact and finitely-convergent MIBLP solver, also addressing MIBLP unboundedness and infeasibility. As in other approaches from the literature, our scheme is finitely-convergent in case both the leader and the follower problems are pure integer. In addition, it is capable of dealing with continuous variables both in the leader and in follower problems—provided that the leader variables influencing follower’s decisions are integer and bounded. We then introduce new classes of linear inequalities to be embedded in this branch-and-bound framework, some of which are intersection cuts based on feasible-free convex sets. We present a computational study on various classes of benchmark instances available from the literature, in which we demonstrate that our approach outperforms alternative state-of-the-art MIBLP methods."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
1 => Essec\Faculty\Model\Contribution {#2341
#_index: "academ_contributions"
#_id: "2182"
#_source: array:18 [
"id" => "2182"
"slug" => "outer-approximation-and-submodular-cuts-for-maximum-capture-facility-location-problems-with-random-utilities"
"yearMonth" => "2018-04"
"year" => "2018"
"title" => "Outer Approximation and Submodular Cuts for Maximum Capture Facility Location Problems with Random Utilities"
"description" => "LJUBIC, I. et MORENO, E. (2018). Outer Approximation and Submodular Cuts for Maximum Capture Facility Location Problems with Random Utilities. <i>European Journal of Operational Research</i>, 266(1), pp. 46-56."
"authors" => array:2 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "MORENO E."
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Combinatorial optimization"
1 => "Branch-and-cut"
2 => "Maximum capture"
3 => "Random utility model"
4 => "Competitive facility location"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0377221717308445"
"publicationInfo" => array:3 [
"pages" => "46-56"
"volume" => "266"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We consider a family of competitive facility location problems in which a “newcomer” company enters the market and has to decide where to locate a set of new facilities so as to maximize its market share. The multinomial logit model is used to estimate the captured customer demand. We propose a first branch-and-cut approach for this family of difficult mixed-integer non-linear problems. Our approach combines two types of cutting planes that exploit particular properties of the objective function: the first one are the outer-approximation cuts and the second one are the submodular cuts.The approach is computationally evaluated on three datasets from the recent literature. The obtained results show that our new branch-and-cut drastically outperforms state-of-the-art exact approaches, both in terms of the computing times, and in terms of the number of instances solved to optimality."
"en" => "We consider a family of competitive facility location problems in which a “newcomer” company enters the market and has to decide where to locate a set of new facilities so as to maximize its market share. The multinomial logit model is used to estimate the captured customer demand. We propose a first branch-and-cut approach for this family of difficult mixed-integer non-linear problems. Our approach combines two types of cutting planes that exploit particular properties of the objective function: the first one are the outer-approximation cuts and the second one are the submodular cuts.The approach is computationally evaluated on three datasets from the recent literature. The obtained results show that our new branch-and-cut drastically outperforms state-of-the-art exact approaches, both in terms of the computing times, and in terms of the number of instances solved to optimality."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
2 => Essec\Faculty\Model\Contribution {#2343
#_index: "academ_contributions"
#_id: "2384"
#_source: array:18 [
"id" => "2384"
"slug" => "redesigning-benders-decomposition-for-large-scale-facility-location"
"yearMonth" => "2017-07"
"year" => "2017"
"title" => "Redesigning Benders Decomposition for Large-Scale Facility Location"
"description" => "FISCHETTI, M., LJUBIC, I. et SINNL, M. (2017). Redesigning Benders Decomposition for Large-Scale Facility Location. <i>Management Science</i>, 63(7), pp. 2146-2162."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "FISCHETTI M."
]
2 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.researchgate.net/publication/304187587_Redesigning_Benders_Decomposition_for_Large-Scale_Facility_Location"
"publicationInfo" => array:3 [
"pages" => "2146-2162"
"volume" => "63"
"number" => "7"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The uncapacitated facility location (UFL) problem is one of the most famous and most studied problems in the operations research literature. Given a set of potential facility locations and a set of customers, the goal is to find a subset of facility locations to open and to allocate each customer to open facilities so that the facility opening plus customer allocation costs are minimized. In our setting, for each customer the allocation cost is assumed to be a linear or separable convex quadratic function. Motivated by recent UFL applications in business analytics, we revise approaches that work on a projected decision space and hence are intrinsically more scalable for large-scale input data. Our working hypothesis is that many of the exact (decomposition) approaches that were proposed decades ago and discarded soon after need to be redesigned to take advantage of the new hardware and software technologies. To this end, we “thin out” the classical models from the literature and use (generalized) Benders cuts to replace a huge number of allocation variables by a small number of continuous variables that model the customer allocation cost directly. Our results show that Benders decomposition allows for a significant boost in the performance of a mixed-integer programming solver. We report the optimal solution of a large set of previously unsolved benchmark instances widely used in the available literature. In particular, dramatic speedups are achieved for UFL problems with separable quadratic allocation costs, which turn out to be much easier than their linear counterparts when our approach is used."
"en" => "The uncapacitated facility location (UFL) problem is one of the most famous and most studied problems in the operations research literature. Given a set of potential facility locations and a set of customers, the goal is to find a subset of facility locations to open and to allocate each customer to open facilities so that the facility opening plus customer allocation costs are minimized. In our setting, for each customer the allocation cost is assumed to be a linear or separable convex quadratic function. Motivated by recent UFL applications in business analytics, we revise approaches that work on a projected decision space and hence are intrinsically more scalable for large-scale input data. Our working hypothesis is that many of the exact (decomposition) approaches that were proposed decades ago and discarded soon after need to be redesigned to take advantage of the new hardware and software technologies. To this end, we “thin out” the classical models from the literature and use (generalized) Benders cuts to replace a huge number of allocation variables by a small number of continuous variables that model the customer allocation cost directly. Our results show that Benders decomposition allows for a significant boost in the performance of a mixed-integer programming solver. We report the optimal solution of a large set of previously unsolved benchmark instances widely used in the available literature. In particular, dramatic speedups are achieved for UFL problems with separable quadratic allocation costs, which turn out to be much easier than their linear counterparts when our approach is used."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
3 => Essec\Faculty\Model\Contribution {#2340
#_index: "academ_contributions"
#_id: "2501"
#_source: array:18 [
"id" => "2501"
"slug" => "solving-minimum-cost-shared-arborescence-problems"
"yearMonth" => "2017-05"
"year" => "2017"
"title" => "Solving Minimum-Cost Shared Arborescence Problems"
"description" => "ÁLVAREZ-MIRANDA, E., LJUBIC, I., LUIPERSBECK, M. et SINNL, M. (2017). Solving Minimum-Cost Shared Arborescence Problems. <i>European Journal of Operational Research</i>, 258(3), pp. 887-901."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "ÁLVAREZ-MIRANDA E."
]
2 => array:1 [
"name" => "LUIPERSBECK M."
]
3 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://doi.org/10.1016/j.ejor.2016.11.004"
"publicationInfo" => array:3 [
"pages" => "887-901"
"volume" => "258"
"number" => "3"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In this work, we consider the minimum-cost shared Steiner arborescence problem (SStA). In this problem, the goal is to find a minimum-cost subgraph, which is shared among multiple entities and each entity is able to establish a cost-efficient Steiner arborescence. The SStA has been recently used in the literature to establish shared functional modules in protein-protein interaction networks. We propose a cut-based formulation for the problem, and design two exact algorithmic approaches: one based on the separation of connectivity cut inequalities, and the other corresponding to a Benders decomposition of the former model. Both approaches are enhanced by various techniques, including (i) preprocessing, (ii) stabilized cut generation, (iii) primal heuristics, and (iv) cut management. These two algorithmic alternatives are computationally evaluated and compared with a previously proposed flow- based formulation. We illustrate the effectiveness of the algorithms on two types of instances derived from protein-protein interaction networks (available from the previous literature) and from telecommunication access networks."
"en" => "In this work, we consider the minimum-cost shared Steiner arborescence problem (SStA). In this problem, the goal is to find a minimum-cost subgraph, which is shared among multiple entities and each entity is able to establish a cost-efficient Steiner arborescence. The SStA has been recently used in the literature to establish shared functional modules in protein-protein interaction networks. We propose a cut-based formulation for the problem, and design two exact algorithmic approaches: one based on the separation of connectivity cut inequalities, and the other corresponding to a Benders decomposition of the former model. Both approaches are enhanced by various techniques, including (i) preprocessing, (ii) stabilized cut generation, (iii) primal heuristics, and (iv) cut management. These two algorithmic alternatives are computationally evaluated and compared with a previously proposed flow- based formulation. We illustrate the effectiveness of the algorithms on two types of instances derived from protein-protein interaction networks (available from the previous literature) and from telecommunication access networks."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
4 => Essec\Faculty\Model\Contribution {#2344
#_index: "academ_contributions"
#_id: "2517"
#_source: array:18 [
"id" => "2517"
"slug" => "stochastic-survivable-network-design-problems-theory-and-practice"
"yearMonth" => "2017-01"
"year" => "2017"
"title" => "Stochastic Survivable Network Design Problems: Theory and Practice"
"description" => "LJUBIC, I., MUTZEL, P. et ZEY, B. (2017). Stochastic Survivable Network Design Problems: Theory and Practice. <i>European Journal of Operational Research</i>, 256(2), pp. 333-348."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "MUTZEL P."
]
2 => array:1 [
"name" => "ZEY B."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://doi.org/10.1016/j.ejor.2016.06.048"
"publicationInfo" => array:3 [
"pages" => "333-348"
"volume" => "256"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We study survivable network design problems with edge-connectivity requirements under a two-stage stochastic model with recourse and finitely many scenarios. For the formulation in the natural space of edge variables we show that facet defining inequalities of the underlying polytope can be derived from the deterministic counterparts. Moreover, by using graph orientation properties we introduce stronger cut-based formulations. For solving the proposed mixed integer programing models, we suggest a two- stage branch&cut algorithm based on a decomposed model. In order to accelerate the computations, we suggest a new technique for strengthening the decomposed L-shaped optimality cuts which is computa- tionally fast and easy to implement. A computational study shows the benefit of the decomposition and the cut strengthening –which significantly reduces the number of master iterations and the computa- tional running time. Moreover, we evaluate the stability of the scenario generation method and analyze the value of the stochastic solution."
"en" => "We study survivable network design problems with edge-connectivity requirements under a two-stage stochastic model with recourse and finitely many scenarios. For the formulation in the natural space of edge variables we show that facet defining inequalities of the underlying polytope can be derived from the deterministic counterparts. Moreover, by using graph orientation properties we introduce stronger cut-based formulations. For solving the proposed mixed integer programing models, we suggest a two- stage branch&cut algorithm based on a decomposed model. In order to accelerate the computations, we suggest a new technique for strengthening the decomposed L-shaped optimality cuts which is computa- tionally fast and easy to implement. A computational study shows the benefit of the decomposition and the cut strengthening –which significantly reduces the number of master iterations and the computa- tional running time. Moreover, we evaluate the stability of the scenario generation method and analyze the value of the stochastic solution."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
5 => Essec\Faculty\Model\Contribution {#2338
#_index: "academ_contributions"
#_id: "2705"
#_source: array:18 [
"id" => "2705"
"slug" => "the-recoverable-robust-facility-location-problem"
"yearMonth" => "2015-09"
"year" => "2015"
"title" => "The Recoverable Robust Facility Location Problem"
"description" => "ÁLVAREZ-MIRANDA, E., FERNÁNDEZ, E. et LJUBIC, I. (2015). The Recoverable Robust Facility Location Problem. <i>Transportation Research Part B: Methodological</i>, 79(1), pp. 93-120."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "ÁLVAREZ-MIRANDA E."
]
2 => array:1 [
"name" => "FERNÁNDEZ E."
]
]
"ouvrage" => ""
"keywords" => array:4 [
0 => "Facility location"
1 => "Two-stage robust optimization"
2 => "Branch-and-cut"
3 => "L-shaped cuts"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0191261515001228"
"publicationInfo" => array:3 [
"pages" => "93-120"
"volume" => "79"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
This work deals with a facility location problem in which location and allocation (transportation) policy is defined in two stages such that a first-stage solution should be robust against the possible realizations (scenarios) of the input data that can only be revealed in a second stage. This solution should be robust enough so that it can be recovered promptly and at low cost in the second stage. In contrast to some related modeling approaches from the literature, this new recoverable robust model is more general in terms of the considered data uncertainty; it can address situations in which uncertainty may be present in any of the following four categories: provider-side uncertainty, receiver-side uncertainty, uncertainty in-between, and uncertainty with respect to the cost parameters.\n
For this novel problem, a sophisticated branch-and-cut framework based on Benders decomposition is designed and complemented by several non-trivial enhancements, including scenario sorting, dual lifting, branching priorities, matheuristics and zero-half cuts. Two large sets of instances that incorporate spatial and demographic information of countries such as Germany and US (transportation) and Bangladesh and the Philippines (disaster management) are introduced. They are used to analyze in detail the characteristics of the proposed model and the obtained solutions as well as the effectiveness, behavior and limitations of the designed algorithm.
"""
"en" => """
This work deals with a facility location problem in which location and allocation (transportation) policy is defined in two stages such that a first-stage solution should be robust against the possible realizations (scenarios) of the input data that can only be revealed in a second stage. This solution should be robust enough so that it can be recovered promptly and at low cost in the second stage. In contrast to some related modeling approaches from the literature, this new recoverable robust model is more general in terms of the considered data uncertainty; it can address situations in which uncertainty may be present in any of the following four categories: provider-side uncertainty, receiver-side uncertainty, uncertainty in-between, and uncertainty with respect to the cost parameters.\n
For this novel problem, a sophisticated branch-and-cut framework based on Benders decomposition is designed and complemented by several non-trivial enhancements, including scenario sorting, dual lifting, branching priorities, matheuristics and zero-half cuts. Two large sets of instances that incorporate spatial and demographic information of countries such as Germany and US (transportation) and Bangladesh and the Philippines (disaster management) are introduced. They are used to analyze in detail the characteristics of the proposed model and the obtained solutions as well as the effectiveness, behavior and limitations of the designed algorithm.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
6 => Essec\Faculty\Model\Contribution {#2342
#_index: "academ_contributions"
#_id: "2744"
#_source: array:18 [
"id" => "2744"
"slug" => "thinning-out-steiner-trees-a-node-based-model-for-uniform-edge-costs"
"yearMonth" => "2017-06"
"year" => "2017"
"title" => "Thinning out Steiner Trees: A Node-Based Model for Uniform Edge Costs"
"description" => "FISCHETTI, M., LEITNER, M., LJUBIC, I., LUIPERSBECK, M., MONACI, M. et RESCH, M. (2017). Thinning out Steiner Trees: A Node-Based Model for Uniform Edge Costs. <i>Mathematical Programming Computation</i>, 9(2), pp. 203-229."
"authors" => array:6 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "FISCHETTI M."
]
2 => array:1 [
"name" => "LEITNER M."
]
3 => array:1 [
"name" => "LUIPERSBECK M."
]
4 => array:1 [
"name" => "MONACI M."
]
5 => array:1 [
"name" => "RESCH M."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://link.springer.com/article/10.1007/s12532-016-0111-0"
"publicationInfo" => array:3 [
"pages" => "203-229"
"volume" => "9"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The Steiner tree problem is a challenging NP-hard problem. Many hard instances of this problem are publicly available, that are still unsolved by state-of-the-art branch-and-cut codes. A typical strategy to attack these instances is to enrich the polyhedral description of the problem, and/or to implement more and more sophisticated separation procedures and branching strategies. In this paper we investigate the opposite viewpoint, and try to make the solution method as simple as possible while working on the modeling side. Our working hypothesis is that the extreme hardness of some classes of instances mainly comes from over-modeling, and that some instances can become quite easy to solve when a simpler model is considered. In other words, we aim at “thinning out” the usual models for the sake of getting a more agile framework. In particular, we focus on a model that only involves node variables, which is rather appealing for the “uniform” cases where all edges have the same cost. In our computational study, we first show that this new model allows one to quickly produce very good (sometimes proven optimal) solutions for notoriously hard instances from the literature. In some cases, our approach takes just few seconds to prove optimality for instances never solved (even after days of computation) by the standard methods. Moreover, we report improved solutions for several SteinLib instances, including the (in)famous hypercube ones. We also demonstrate how to build a unified solver on top of the new node-based model and the previous state-of-the-art model (defined in the space of arc and node variables). The solver relies on local branching, initialization heuristics, preprocessing and local search procedures. A filtering mechanism is applied to automatically select the best algorithmic ingredients for each instance individually. The presented solver is the winner of the DIMACS Challenge on Steiner trees in most of the considered categories."
"en" => "The Steiner tree problem is a challenging NP-hard problem. Many hard instances of this problem are publicly available, that are still unsolved by state-of-the-art branch-and-cut codes. A typical strategy to attack these instances is to enrich the polyhedral description of the problem, and/or to implement more and more sophisticated separation procedures and branching strategies. In this paper we investigate the opposite viewpoint, and try to make the solution method as simple as possible while working on the modeling side. Our working hypothesis is that the extreme hardness of some classes of instances mainly comes from over-modeling, and that some instances can become quite easy to solve when a simpler model is considered. In other words, we aim at “thinning out” the usual models for the sake of getting a more agile framework. In particular, we focus on a model that only involves node variables, which is rather appealing for the “uniform” cases where all edges have the same cost. In our computational study, we first show that this new model allows one to quickly produce very good (sometimes proven optimal) solutions for notoriously hard instances from the literature. In some cases, our approach takes just few seconds to prove optimality for instances never solved (even after days of computation) by the standard methods. Moreover, we report improved solutions for several SteinLib instances, including the (in)famous hypercube ones. We also demonstrate how to build a unified solver on top of the new node-based model and the previous state-of-the-art model (defined in the space of arc and node variables). The solver relies on local branching, initialization heuristics, preprocessing and local search procedures. A filtering mechanism is applied to automatically select the best algorithmic ingredients for each instance individually. The presented solver is the winner of the DIMACS Challenge on Steiner trees in most of the considered categories."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
7 => Essec\Faculty\Model\Contribution {#2345
#_index: "academ_contributions"
#_id: "2746"
#_source: array:18 [
"id" => "2746"
"slug" => "tighter-mip-models-for-barge-container-ship-routing"
"yearMonth" => "2019-01"
"year" => "2019"
"title" => "Tighter MIP models for Barge Container Ship Routing"
"description" => "ALFANDARI, L., DAVIDOVIC, T., FURINI, F., LJUBIC, I., MARAS, V. et MARTIN, S. (2019). Tighter MIP models for Barge Container Ship Routing. <i>Omega</i>, 82, pp. 38-54."
"authors" => array:6 [
0 => array:3 [
"name" => "ALFANDARI Laurent"
"bid" => "B00000901"
"slug" => "alfandari-laurent"
]
1 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
2 => array:1 [
"name" => "DAVIDOVIC Tatjana"
]
3 => array:1 [
"name" => "FURINI Fabio"
]
4 => array:1 [
"name" => "MARAS Vladislav"
]
5 => array:1 [
"name" => "MARTIN Sébastien"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Containers"
1 => "Programmation linéaire"
2 => "Repositionnement"
3 => "Routage"
4 => "Transport"
]
"updatedAt" => "2022-10-10 15:01:07"
"publicationUrl" => "https://doi.org/10.1016/j.omega.2017.12.002"
"publicationInfo" => array:3 [
"pages" => "38-54"
"volume" => "82"
"number" => ""
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "On considère la conception d'une ligne de transport fluvial devant décider à quels ports s'arrêter pour transporter des demandes de containers entre ports. Les nouveaux modèles proposés surpassent les modèles existants de la littérature. Ils exploitent la structure en ligne du routage en modélisant ce dernier par des variables associées aux noeuds (ports), et intègrent des variables associées soit aux arcs soit aux noeuds du réseau de transport pour le repositionnement des containers vides. Ce dernier modèle est le plus performant, particulièrement dans le cas de demandes non sécables."
"en" => "We consider Barge Container Ship Routing with empty container repositioning. We design new MIP formulations that outperfom state-of-the-art models. The new models exploit the line structure of inland waterway transportation by modeling routing with node variables, and consider either node or arc variables for empty containers. The second formulation reveals to be the most efficient one, especially for unsplittable demands. We also optimize the turnaround time or size of the fleet."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
8 => Essec\Faculty\Model\Contribution {#2346
#_index: "academ_contributions"
#_id: "532"
#_source: array:18 [
"id" => "532"
"slug" => "a-dual-ascent-based-branch-and-bound-framework-for-the-prize-collecting-steiner-tree-and-related-problems"
"yearMonth" => "2018-04"
"year" => "2018"
"title" => "A Dual Ascent-Based Branch-and-Bound Framework for the Prize-Collecting Steiner Tree and Related Problems"
"description" => "LEITNER, M., LJUBIC, I., LUIPERSBECK, M. et SINNL, M. (2018). A Dual Ascent-Based Branch-and-Bound Framework for the Prize-Collecting Steiner Tree and Related Problems. <i>INFORMS Journal on Computing</i>, 30(2), pp. 402-420."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "LEITNER M."
]
2 => array:1 [
"name" => "LUIPERSBECK M."
]
3 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.researchgate.net/publication/325373192_A_Dual_Ascent-Based_Branch-and-Bound_Framework_for_the_Prize-Collecting_Steiner_Tree_and_Related_Problems"
"publicationInfo" => array:3 [
"pages" => "402-420"
"volume" => "30"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We present a branch-and-bound (B&B) framework for the asymmetric prize-collecting Steiner tree problem (APCSTP). Several well-known network design problems can be transformed to the APCSTP, including the Steiner tree problem (STP), prize-collecting Steiner tree problem (PCSTP), maximum-weight connected subgraph problem (MWCS), and node-weighted Steiner tree problem (NWSTP). The main component of our framework is a new dual ascent algorithm for the rooted APCSTP, which generalizes Wong’s dual ascent algorithm for the Steiner arborescence problem. The lower bounds and dual information obtained from the algorithm are exploited within powerful bound-based reduction tests and for guiding primal heuristics. The framework is complemented by additional alternative-based reduction tests. Extensive computational results on benchmark instances for the PCSTP, MWCS, and NWSTP indicate the framework’s effectiveness, as most instances from literature are solved to optimality within seconds, including most of the (previously unsolved) largest instances from the recent DIMACS Challenge on Steiner trees. Moreover, results on new asymmetric instances for the APCSTP are reported. Since the addressed network design problems are frequently used for modeling various real-world applications (e.g., in bioinformatics), the implementation of the presented B&B framework has been made publicly available."
"en" => "We present a branch-and-bound (B&B) framework for the asymmetric prize-collecting Steiner tree problem (APCSTP). Several well-known network design problems can be transformed to the APCSTP, including the Steiner tree problem (STP), prize-collecting Steiner tree problem (PCSTP), maximum-weight connected subgraph problem (MWCS), and node-weighted Steiner tree problem (NWSTP). The main component of our framework is a new dual ascent algorithm for the rooted APCSTP, which generalizes Wong’s dual ascent algorithm for the Steiner arborescence problem. The lower bounds and dual information obtained from the algorithm are exploited within powerful bound-based reduction tests and for guiding primal heuristics. The framework is complemented by additional alternative-based reduction tests. Extensive computational results on benchmark instances for the PCSTP, MWCS, and NWSTP indicate the framework’s effectiveness, as most instances from literature are solved to optimality within seconds, including most of the (previously unsolved) largest instances from the recent DIMACS Challenge on Steiner trees. Moreover, results on new asymmetric instances for the APCSTP are reported. Since the addressed network design problems are frequently used for modeling various real-world applications (e.g., in bioinformatics), the implementation of the presented B&B framework has been made publicly available."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
9 => Essec\Faculty\Model\Contribution {#2347
#_index: "academ_contributions"
#_id: "562"
#_source: array:18 [
"id" => "562"
"slug" => "a-new-general-purpose-algorithm-for-mixed-integer-bilevel-linear-programs"
"yearMonth" => "2017-12"
"year" => "2017"
"title" => "A New General-Purpose Algorithm for Mixed-Integer Bilevel Linear Programs"
"description" => "FISCHETTI, M., LJUBIC, I., MONACI, M. et SINNL, M. (2017). A New General-Purpose Algorithm for Mixed-Integer Bilevel Linear Programs. <i>Operations Research</i>, 65(6), pp. 1615-1637."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "FISCHETTI M."
]
2 => array:1 [
"name" => "MONACI M."
]
3 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://pubsonline.informs.org/doi/10.1287/opre.2017.1650"
"publicationInfo" => array:3 [
"pages" => "1615-1637"
"volume" => "65"
"number" => "6"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Bilevel optimization problems are very challenging optimization models arising in many important practical contexts, including pricing mechanisms in the energy sector, airline and telecommunication industry, transportation networks, critical infrastructure defense, and machine learning. In this paper, we consider bilevel programs with continuous and discrete variables at both levels, with linear objectives and constraints (continuous upper level variables, if any, must not appear in the lower level problem). We propose a general-purpose branch-and-cut exact solution method based on several new classes of valid inequalities, which also exploits a very effective bilevel-specific preprocessing procedure. An extensive computational study is presented to evaluate the performance of various solution methods on a common testbed of more than 800 instances from the literature and 60 randomly generated instances. Our new algorithm consistently outperforms (often by a large margin) alternative state-of-the-art methods from the literature, including methods exploiting problem-specific information for special instance classes. In particular, it solves to optimality more than 300 previously unsolved instances from the literature. To foster research on this challenging topic, our solver is made publicly available online."
"en" => "Bilevel optimization problems are very challenging optimization models arising in many important practical contexts, including pricing mechanisms in the energy sector, airline and telecommunication industry, transportation networks, critical infrastructure defense, and machine learning. In this paper, we consider bilevel programs with continuous and discrete variables at both levels, with linear objectives and constraints (continuous upper level variables, if any, must not appear in the lower level problem). We propose a general-purpose branch-and-cut exact solution method based on several new classes of valid inequalities, which also exploits a very effective bilevel-specific preprocessing procedure. An extensive computational study is presented to evaluate the performance of various solution methods on a common testbed of more than 800 instances from the literature and 60 randomly generated instances. Our new algorithm consistently outperforms (often by a large margin) alternative state-of-the-art methods from the literature, including methods exploiting problem-specific information for special instance classes. In particular, it solves to optimality more than 300 previously unsolved instances from the literature. To foster research on this challenging topic, our solver is made publicly available online."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
10 => Essec\Faculty\Model\Contribution {#2348
#_index: "academ_contributions"
#_id: "564"
#_source: array:18 [
"id" => "564"
"slug" => "a-node-based-ilp-formulation-for-the-node-weighted-dominating-steiner-problem"
"yearMonth" => "2017-01"
"year" => "2017"
"title" => "A Node-Based ILP Formulation for the Node-Weighted Dominating Steiner Problem"
"description" => "BLEY, A., LJUBIC, I. et MAURER, O. (2017). A Node-Based ILP Formulation for the Node-Weighted Dominating Steiner Problem. <i>Networks</i>, 69(1), pp. 33-51."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "BLEY A."
]
2 => array:1 [
"name" => "MAURER O."
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Connected dominating set"
1 => "Steiner tree"
2 => "Integer programming"
3 => "Thin formulation"
4 => "Polyhedron"
5 => "Facets"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://onlinelibrary.wiley.com/doi/abs/10.1002/net.21722"
"publicationInfo" => array:3 [
"pages" => "33-51"
"volume" => "69"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In this article, we consider the Node-Weighted Dominating Steiner Problem. Given a graph with node weights and a set of terminal nodes, the goal is to find a connected node-induced subgraph of minimum weight, such that each terminal node is contained in or adjacent to some node in the chosen subgraph. The problem arises in applications in the design of telecommunication networks. Integer programming formulations for Steiner problems usually employ a variable for each edge. We introduce a formulation that only uses node variables and that models connectivity through node-cut inequalities, which can be separated in polynomial time. We discuss necessary and sufficient conditions for the model inequalities to define facets and we introduce a class of lifted partition-based inequalities, which can be used to strengthen the linear relaxation. Finally, we show that the polyhedron defined by these inequalities is integral if the underlying graph is a cycle where no two terminals are adjacent. In the general cycle setting, we show that we can get a complete description of the feasible solutions by lifting and projecting into a polytope with no more than twice the dimension. We also show that the well-known indegree equalities are implied by the lifted partition inequalities. Finally, we evaluate the effectiveness of the presented partition inequalities in computational experiments."
"en" => "In this article, we consider the Node-Weighted Dominating Steiner Problem. Given a graph with node weights and a set of terminal nodes, the goal is to find a connected node-induced subgraph of minimum weight, such that each terminal node is contained in or adjacent to some node in the chosen subgraph. The problem arises in applications in the design of telecommunication networks. Integer programming formulations for Steiner problems usually employ a variable for each edge. We introduce a formulation that only uses node variables and that models connectivity through node-cut inequalities, which can be separated in polynomial time. We discuss necessary and sufficient conditions for the model inequalities to define facets and we introduce a class of lifted partition-based inequalities, which can be used to strengthen the linear relaxation. Finally, we show that the polyhedron defined by these inequalities is integral if the underlying graph is a cycle where no two terminals are adjacent. In the general cycle setting, we show that we can get a complete description of the feasible solutions by lifting and projecting into a polytope with no more than twice the dimension. We also show that the well-known indegree equalities are implied by the lifted partition inequalities. Finally, we evaluate the effectiveness of the presented partition inequalities in computational experiments."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
11 => Essec\Faculty\Model\Contribution {#2349
#_index: "academ_contributions"
#_id: "565"
#_source: array:18 [
"id" => "565"
"slug" => "a-node-based-layered-graph-approach-for-the-steiner-tree-problem-with-revenues-budget-and-hop-constraints"
"yearMonth" => "2016-12"
"year" => "2016"
"title" => "A Node-Based Layered Graph Approach for the Steiner Tree Problem with Revenues, Budget and Hop-Constraints"
"description" => "SINNL, M. et LJUBIC, I. (2016). A Node-Based Layered Graph Approach for the Steiner Tree Problem with Revenues, Budget and Hop-Constraints. <i>Mathematical Programming Computation</i>, 8(4), pp. 461–490."
"authors" => array:2 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Mixed integer programming"
1 => "Exact computation"
2 => "Hop-constrained trees"
3 => "Branch-and-cut"
4 => "Layered graph"
5 => "Node-based model"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://link.springer.com/article/10.1007/s12532-016-0102-1"
"publicationInfo" => array:3 [
"pages" => "461–490"
"volume" => "8"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The Steiner tree problem with revenues, budget and hop-constraints (STPRBH) is a variant of the classical Steiner tree problem. The goal is to find a tree maximizing the collected revenue, which is associated with nodes, subject to a given budget for the edge cost of the tree and a hop-limit for the distance between the given root node and any other node in that tree. In this work, we introduce a novel generic way to model hop-constrained tree problems as integer linear programs and apply it to the STPRBH. Our approach is based on the concept of layered graphs that gained widespread attention in the recent years, due to their computational advantage when compared to previous formulations for modeling hop-constraints. Contrary to previous MIP formulations based on layered graphs (that are arc-based models), our model is node-based. Thus it contains much less variables and allows to tackle large-scale instances and/or instances with large hop-limits, for which the size of arc-based layered graph models may become prohibitive. The aim of our model is to provide a good compromise between quality of root relaxation bounds and the size of the underlying MIP formulation. We implemented a branch-and-cut algorithm for the STPRBH based on our new model. Most of the instances available for the DIMACS challenge, including 78 (out of 86) previously unsolved ones, can be solved to proven optimality within a time limit of 1000 s, most of them being solved within a few seconds only. These instances contain up to 500 nodes and 12,500 edges, with hop-limit up to 25."
"en" => "The Steiner tree problem with revenues, budget and hop-constraints (STPRBH) is a variant of the classical Steiner tree problem. The goal is to find a tree maximizing the collected revenue, which is associated with nodes, subject to a given budget for the edge cost of the tree and a hop-limit for the distance between the given root node and any other node in that tree. In this work, we introduce a novel generic way to model hop-constrained tree problems as integer linear programs and apply it to the STPRBH. Our approach is based on the concept of layered graphs that gained widespread attention in the recent years, due to their computational advantage when compared to previous formulations for modeling hop-constraints. Contrary to previous MIP formulations based on layered graphs (that are arc-based models), our model is node-based. Thus it contains much less variables and allows to tackle large-scale instances and/or instances with large hop-limits, for which the size of arc-based layered graph models may become prohibitive. The aim of our model is to provide a good compromise between quality of root relaxation bounds and the size of the underlying MIP formulation. We implemented a branch-and-cut algorithm for the STPRBH based on our new model. Most of the instances available for the DIMACS challenge, including 78 (out of 86) previously unsolved ones, can be solved to proven optimality within a time limit of 1000 s, most of them being solved within a few seconds only. These instances contain up to 500 nodes and 12,500 edges, with hop-limit up to 25."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
12 => Essec\Faculty\Model\Contribution {#2350
#_index: "academ_contributions"
#_id: "617"
#_source: array:18 [
"id" => "617"
"slug" => "an-algorithmic-framework-for-the-exact-solution-of-tree-star-problems"
"yearMonth" => "2017-06"
"year" => "2017"
"title" => "An Algorithmic Framework for the Exact Solution of Tree-Star Problems"
"description" => "LEITNER, M., LJUBIC, I., SALAZAR-GONZALEZ, J.J. et SINNL, M. (2017). An Algorithmic Framework for the Exact Solution of Tree-Star Problems. <i>European Journal of Operational Research</i>, 1(261), pp. 54-66."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "LEITNER M."
]
2 => array:1 [
"name" => "SALAZAR-GONZALEZ J.-J."
]
3 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Combinatorial optimization"
1 => "Connected facility location"
2 => "Branch-and-cut"
3 => "Dual ascent"
4 => "Benders decomposition"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0377221717301170"
"publicationInfo" => array:3 [
"pages" => "54-66"
"volume" => "1"
"number" => "261"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Many problems arising in the area of telecommunication ask for solutions with a tree-star topology. This paper proposes a general procedure for finding optimal solutions to a family of these problems. The family includes problems in the literature named as connected facility location, rent-or-buy and generalized Steiner tree-star. We propose a solution framework based on a branch-and-cut algorithm which also relies on sophisticated reduction and heuristic techniques. An important ingredient of this framework is a dual ascent procedure for asymmetric connected facility location. This paper shows how this procedure can be exploited in combination with various mixed integer programming formulations. Using the new framework, many benchmark instances in the literature for which only heuristic results were available so far, can be solved to provable optimality within seconds. To better assess the computational performance of the new approach, we additionally consider larger instances and provide optimal solutions for most of them too."
"en" => "Many problems arising in the area of telecommunication ask for solutions with a tree-star topology. This paper proposes a general procedure for finding optimal solutions to a family of these problems. The family includes problems in the literature named as connected facility location, rent-or-buy and generalized Steiner tree-star. We propose a solution framework based on a branch-and-cut algorithm which also relies on sophisticated reduction and heuristic techniques. An important ingredient of this framework is a dual ascent procedure for asymmetric connected facility location. This paper shows how this procedure can be exploited in combination with various mixed integer programming formulations. Using the new framework, many benchmark instances in the literature for which only heuristic results were available so far, can be solved to provable optimality within seconds. To better assess the computational performance of the new approach, we additionally consider larger instances and provide optimal solutions for most of them too."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
13 => Essec\Faculty\Model\Contribution {#2351
#_index: "academ_contributions"
#_id: "622"
#_source: array:18 [
"id" => "622"
"slug" => "an-effective-dynamic-programming-algorithm-for-the-minimum-cost-maximal-knapsack-packing-problem"
"yearMonth" => "2017-10"
"year" => "2017"
"title" => "An Effective Dynamic Programming Algorithm for the Minimum-Cost Maximal Knapsack Packing Problem"
"description" => "FURINI, F., LJUBIC, I. et SINNL, M. (2017). An Effective Dynamic Programming Algorithm for the Minimum-Cost Maximal Knapsack Packing Problem. <i>European Journal of Operational Research</i>, 262(2), pp. 438-448."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "FURINI F."
]
2 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Combinatorial optimization"
1 => "Maximal knapsack packing"
2 => "Minimal knapsack cover"
3 => "Dynamic programming"
4 => "Integer programming"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0377221717302928"
"publicationInfo" => array:3 [
"pages" => "438-448"
"volume" => "262"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Given a set of items with profits and weights and a knapsack capacity, we study the problem of finding a maximal knapsack packing that minimizes the profit of the selected items. We propose an effective dynamic programming (DP) algorithm which has a pseudo-polynomial time complexity. We demonstrate the equivalence between this problem and the problem of finding a minimal knapsack cover that maximizes the profit of the selected items. In an extensive computational study on a large and diverse set of benchmark instances, we demonstrate that the new DP algorithm outperforms a state-of-the-art commercial mixed-integer programming (MIP) solver applied to the two best performing MIP models from the literature."
"en" => "Given a set of items with profits and weights and a knapsack capacity, we study the problem of finding a maximal knapsack packing that minimizes the profit of the selected items. We propose an effective dynamic programming (DP) algorithm which has a pseudo-polynomial time complexity. We demonstrate the equivalence between this problem and the problem of finding a minimal knapsack cover that maximizes the profit of the selected items. In an extensive computational study on a large and diverse set of benchmark instances, we demonstrate that the new DP algorithm outperforms a state-of-the-art commercial mixed-integer programming (MIP) solver applied to the two best performing MIP models from the literature."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
14 => Essec\Faculty\Model\Contribution {#2352
#_index: "academ_contributions"
#_id: "717"
#_source: array:18 [
"id" => "717"
"slug" => "benders-decomposition-for-very-large-scale-partial-set-covering-and-maximal-covering-location-problems"
"yearMonth" => "2019-06"
"year" => "2019"
"title" => "Benders Decomposition for Very Large Scale Partial Set Covering and Maximal Covering Location Problems"
"description" => "CORDEAU, J.F., FURINI, F. et LJUBIC, I. (2019). Benders Decomposition for Very Large Scale Partial Set Covering and Maximal Covering Location Problems. <i>European Journal of Operational Research</i>, 275(3), pp. 882-896."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "CORDEAU Jean-François"
]
2 => array:1 [
"name" => "FURINI Fabio"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Combinatorial optimization"
1 => "Location problems"
2 => "Covering"
3 => "Benders decomposition"
4 => "Branch-and-cut algorithms"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0377221718310737?via%3Dihub"
"publicationInfo" => array:3 [
"pages" => "882-896"
"volume" => "275"
"number" => "3"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Covering problems constitute a fundamental family of facility location problems. This paper introduces a new exact algorithm for two important members of this family: (i) the maximal covering location problem (MCLP), which requires finding a subset of facilities that maximizes the amount of customer demand covered while respecting a budget constraint on the cost of the facilities; and (ii) the partial set covering location problem (PSCLP), which minimizes the cost of the open facilities while forcing a certain amount of customer demand to be covered. We study an effective decomposition approach to the two problems based on the branch-and-Benders-cut reformulation. Our new approach is designed for the realistic case in which the number of customers is much larger than the number of potential facility locations. We report the results of a series of computational experiments demonstrating that, thanks to this decomposition techniques, optimal solutions can be found very quickly for some benchmark instances with one hundred potential facility locations and involving up to 15 and 40 million customer demand points for the MCLP and the PSCLP, respectively."
"en" => "Covering problems constitute a fundamental family of facility location problems. This paper introduces a new exact algorithm for two important members of this family: (i) the maximal covering location problem (MCLP), which requires finding a subset of facilities that maximizes the amount of customer demand covered while respecting a budget constraint on the cost of the facilities; and (ii) the partial set covering location problem (PSCLP), which minimizes the cost of the open facilities while forcing a certain amount of customer demand to be covered. We study an effective decomposition approach to the two problems based on the branch-and-Benders-cut reformulation. Our new approach is designed for the realistic case in which the number of customers is much larger than the number of potential facility locations. We report the results of a series of computational experiments demonstrating that, thanks to this decomposition techniques, optimal solutions can be found very quickly for some benchmark instances with one hundred potential facility locations and involving up to 15 and 40 million customer demand points for the MCLP and the PSCLP, respectively."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
15 => Essec\Faculty\Model\Contribution {#2353
#_index: "academ_contributions"
#_id: "718"
#_source: array:18 [
"id" => "718"
"slug" => "benders-decomposition-without-separability-a-computational-study-for-capacitated-facility-location-problems"
"yearMonth" => "2016-09"
"year" => "2016"
"title" => "Benders Decomposition without Separability: A Computational Study for Capacitated Facility Location Problems"
"description" => "FICHETTI, M., LJUBIC, I. et SINNL, M. (2016). Benders Decomposition without Separability: A Computational Study for Capacitated Facility Location Problems. <i>European Journal of Operational Research</i>, 253(3), pp. 557-569."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "FICHETTI M."
]
2 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Benders decomposition"
1 => "Congested capacitated facility location"
2 => "Perspective reformulation"
3 => "Branch-and-cut"
4 => "Mixed-integer convex programming"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0377221716301126"
"publicationInfo" => array:3 [
"pages" => "557-569"
"volume" => "253"
"number" => "3"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The authors propose a simplified way of deriving Benders cuts for convex optimization. The method is applied to linear / quadratic capacitated facility location problems. For linear case, our Benders method qualifies as one of the best exact solvers. For quadratic case, our Benders method is by far the best available exact solver. Our Benders heuristics outperform previous proposals from the literature"
"en" => "The authors propose a simplified way of deriving Benders cuts for convex optimization. The method is applied to linear / quadratic capacitated facility location problems. For linear case, our Benders method qualifies as one of the best exact solvers. For quadratic case, our Benders method is by far the best available exact solver. Our Benders heuristics outperform previous proposals from the literature"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
16 => Essec\Faculty\Model\Contribution {#2354
#_index: "academ_contributions"
#_id: "956"
#_source: array:18 [
"id" => "956"
"slug" => "decomposition-methods-for-the-two-stage-stochastic-steiner-tree-problem"
"yearMonth" => "2018-04"
"year" => "2018"
"title" => "Decomposition Methods for the Two-Stage Stochastic Steiner Tree Problem"
"description" => "LEITNER, M., LJUBIC, I., LUIPERSBECK, M. et SINNL, M. (2018). Decomposition Methods for the Two-Stage Stochastic Steiner Tree Problem. <i>Computational Optimization and Applications</i>, 69(3), pp. 713-752."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "LEITNER M."
]
2 => array:1 [
"name" => "LUIPERSBECK M."
]
3 => array:1 [
"name" => "SINNL M."
]
]
"ouvrage" => ""
"keywords" => array:4 [
0 => "Lagrangian relaxation"
1 => "Benders decomposition"
2 => "Stochastic optimization"
3 => "Steiner trees"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://link.springer.com/article/10.1007%2Fs10589-017-9966-x"
"publicationInfo" => array:3 [
"pages" => "713-752"
"volume" => "69"
"number" => "3"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
A new algorithmic approach for solving the stochastic Steiner tree problem based on three procedures for computing lower bounds (dual ascent, Lagrangian relaxation,Benders decomposition) is introduced. Our method is derived from a new integer linear programming formulation, which is shown to be strongest among all known formulations. The resulting method, which relies on an interplay of the dual information retrieved from the respective dual procedures, computes upper and lower bounds and combines them with several rules for fixing variables in order to decrease the size of problem instances. The effectiveness of our method is compared in an extensive computational study with the state-of-the-art exact approach, which employs a Benders decomposition based on two-stage branch-and-cut, and a genetic algorithm introduced during the DIMACS implementation challenge on Steiner trees. Our results indicate that the presented method significantly outperforms existing ones, both on benchmark\n
instances from literature, as well as on large-scale telecommunication networks.
"""
"en" => """
A new algorithmic approach for solving the stochastic Steiner tree problem based on three procedures for computing lower bounds (dual ascent, Lagrangian relaxation,Benders decomposition) is introduced. Our method is derived from a new integer linear programming formulation, which is shown to be strongest among all known formulations. The resulting method, which relies on an interplay of the dual information retrieved from the respective dual procedures, computes upper and lower bounds and combines them with several rules for fixing variables in order to decrease the size of problem instances. The effectiveness of our method is compared in an extensive computational study with the state-of-the-art exact approach, which employs a Benders decomposition based on two-stage branch-and-cut, and a genetic algorithm introduced during the DIMACS implementation challenge on Steiner trees. Our results indicate that the presented method significantly outperforms existing ones, both on benchmark\n
instances from literature, as well as on large-scale telecommunication networks.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
17 => Essec\Faculty\Model\Contribution {#2355
#_index: "academ_contributions"
#_id: "1161"
#_source: array:18 [
"id" => "1161"
"slug" => "exact-approaches-for-network-design-problem-with-relays"
"yearMonth" => "2020-03"
"year" => "2020"
"title" => "Exact Approaches for Network Design Problem with Relays"
"description" => "LEITNER, M., LJUBIC, I., RIEDLER, M. et RUTHMAIR, M. (2020). Exact Approaches for Network Design Problem with Relays. <i>Omega</i>, 91."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "LEITNER Markus"
]
2 => array:1 [
"name" => "RIEDLER Martin"
]
3 => array:1 [
"name" => "RUTHMAIR Mario"
]
]
"ouvrage" => ""
"keywords" => array:4 [
0 => "Integer programming"
1 => "Networks"
2 => "Layered graphs"
3 => "Telecommunications"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S030504831830183X"
"publicationInfo" => array:3 [
"pages" => null
"volume" => "91"
"number" => null
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We study the directed network design problem with relays (DNDPR) whose aim is to construct a minimum cost network that enables the communication of a given set of origin-destination pairs. Thereby, expensive signal regeneration devices need to be placed to cover communication distances exceeding a predefined threshold. Applications of the DNDPR arise in telecommunications and transportation. We propose two new integer programming formulations for the DNDPR. The first one is a flow-based formulation with a pseudo-polynomial number of variables and constraints and the second is a cut-based formulation with an exponential number of constraints. Fractional distance values are handled efficiently by augmenting both models with an exponentially-sized set of infeasible path constraints. We develop branch-and-cut algorithms and also consider valid inequalities to strengthen the obtained dual bounds and to speed up convergence. The results of our extensive computational study on diverse sets of benchmark instances show that our algorithms outperform the previous state-of-the-art method based on column generation."
"en" => "We study the directed network design problem with relays (DNDPR) whose aim is to construct a minimum cost network that enables the communication of a given set of origin-destination pairs. Thereby, expensive signal regeneration devices need to be placed to cover communication distances exceeding a predefined threshold. Applications of the DNDPR arise in telecommunications and transportation. We propose two new integer programming formulations for the DNDPR. The first one is a flow-based formulation with a pseudo-polynomial number of variables and constraints and the second is a cut-based formulation with an exponential number of constraints. Fractional distance values are handled efficiently by augmenting both models with an exponentially-sized set of infeasible path constraints. We develop branch-and-cut algorithms and also consider valid inequalities to strengthen the obtained dual bounds and to speed up convergence. The results of our extensive computational study on diverse sets of benchmark instances show that our algorithms outperform the previous state-of-the-art method based on column generation."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
18 => Essec\Faculty\Model\Contribution {#2356
#_index: "academ_contributions"
#_id: "1346"
#_source: array:18 [
"id" => "1346"
"slug" => "ilp-heuristics-and-a-new-exact-method-for-bi-objective-0-1-ilps-application-to-fttx-network-design"
"yearMonth" => "2016-08"
"year" => "2016"
"title" => "ILP Heuristics and a New Exact Method for Bi-Objective 0/1 ILPs: Application to FTTx-Network Design"
"description" => "LEITNER, M., LJUBIC, I., SINNL, M. et WERNER, A. (2016). ILP Heuristics and a New Exact Method for Bi-Objective 0/1 ILPs: Application to FTTx-Network Design. <i>Computers & Operations Research</i>, 72, pp. 128-146."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "LEITNER M."
]
2 => array:1 [
"name" => "SINNL M."
]
3 => array:1 [
"name" => "WERNER A."
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Bi-objective connected facility location"
1 => "k-architecture connected facility location"
2 => "Branch-and-cut"
3 => "Local branching"
4 => "Neighborhood search"
5 => "ILP heuristics"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0305054816300302"
"publicationInfo" => array:3 [
"pages" => "128-146"
"volume" => "72"
"number" => null
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We focus on bi-objective optimization problems whose feasible solutions can be described as 0/1 integer linear programs and propose two ILP heuristics, boundary induced neighborhood search (BINS) and directional local branching. Their main idea is to combine the features and explore the neighborhoods of solutions that are relatively close in the objective space. A two-phase ILP-based heuristic framework relying on BINS and directional local branching is introduced. Moreover, a new exact method called adaptive search in objective space (ASOS) is also proposed. ASOS combines features of the e-constraint method with the binary search in the objective space and uses heuristic solutions produced by BINS for guidance. Our new methods are computationally evaluated on two problems of particular relevance for the design of FTTx-networks. Comparison with other known exact methods (relying on the exploration of the objective space) is conducted on a set of realistic benchmark instances representing telecommunication access networks from Germany."
"en" => "We focus on bi-objective optimization problems whose feasible solutions can be described as 0/1 integer linear programs and propose two ILP heuristics, boundary induced neighborhood search (BINS) and directional local branching. Their main idea is to combine the features and explore the neighborhoods of solutions that are relatively close in the objective space. A two-phase ILP-based heuristic framework relying on BINS and directional local branching is introduced. Moreover, a new exact method called adaptive search in objective space (ASOS) is also proposed. ASOS combines features of the e-constraint method with the binary search in the objective space and uses heuristic solutions produced by BINS for guidance. Our new methods are computationally evaluated on two problems of particular relevance for the design of FTTx-networks. Comparison with other known exact methods (relying on the exploration of the objective space) is conducted on a set of realistic benchmark instances representing telecommunication access networks from Germany."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
19 => Essec\Faculty\Model\Contribution {#2357
#_index: "academ_contributions"
#_id: "8299"
#_source: array:18 [
"id" => "8299"
"slug" => "onlast-mile-delivery-with-autonomous-robots"
"yearMonth" => "2019-06"
"year" => "2019"
"title" => "Onlast-mile Delivery with Autonomous Robots"
"description" => "ALFANDARI, L., LJUBIC, I. et DE MELO DA SILVA, M. (2019). <i>Onlast-mile Delivery with Autonomous Robots</i>. ESSEC Business School."
"authors" => array:3 [
0 => array:3 [
"name" => "ALFANDARI Laurent"
"bid" => "B00000901"
"slug" => "alfandari-laurent"
]
1 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
2 => array:1 [
"name" => "DE MELO DA SILVA M."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Documents de travail"
"en" => "Working Papers"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
20 => Essec\Faculty\Model\Contribution {#2358
#_index: "academ_contributions"
#_id: "8538"
#_source: array:18 [
"id" => "8538"
"slug" => "european-journal-of-operational-research"
"yearMonth" => "2017-06"
"year" => "2017"
"title" => "European Journal of Operational Research"
"description" => "EHRGOTT, M., LJUBIC, I. et PARRAGH, S.N. (2017). European Journal of Operational Research. <i>European Journal of Operational Research</i>, 260(3)."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "EHRGOTT M."
]
2 => array:1 [
"name" => "PARRAGH S. N."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => "260"
"number" => "3"
]
"type" => array:2 [
"fr" => "Editeur invité d'un numéro spécial"
"en" => "Guest editor of a journal special issue"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The development of exact methods for multi-objective optimisation is experiencing increasing interest in the OR community as witnessed by the growing body of research emerging from that domain. Recent advances in the development of nonlinear, linear and mixed integer optimisation solvers push the boundaries towards more challenging areas. Hence solving to optimality larger, more difficult (real-world) problems involving several conflicting objectives, has been put within reach. As guest editors we hope that this feature cluster increases the visibility of research concerning exact methods for multi-objective optimisation and to motivate a broader group of researchers to contribute to the field. It presents a collection of the latest research results on exact algorithms for multi-objective optimisation as well as heuristics derived from exact methods."
"en" => "The development of exact methods for multi-objective optimisation is experiencing increasing interest in the OR community as witnessed by the growing body of research emerging from that domain. Recent advances in the development of nonlinear, linear and mixed integer optimisation solvers push the boundaries towards more challenging areas. Hence solving to optimality larger, more difficult (real-world) problems involving several conflicting objectives, has been put within reach. As guest editors we hope that this feature cluster increases the visibility of research concerning exact methods for multi-objective optimisation and to motivate a broader group of researchers to contribute to the field. It presents a collection of the latest research results on exact algorithms for multi-objective optimisation as well as heuristics derived from exact methods."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
21 => Essec\Faculty\Model\Contribution {#2359
#_index: "academ_contributions"
#_id: "10549"
#_source: array:18 [
"id" => "10549"
"slug" => "hop-constrained-steiner-trees-with-multiple-root-nodes"
"yearMonth" => "2014-06"
"year" => "2014"
"title" => "Hop constrained Steiner trees with multiple root nodes"
"description" => "GOUVEIA, L., LEITNER, M. et LJUBIC, I. (2014). Hop constrained Steiner trees with multiple root nodes. <i>European Journal of Operational Research</i>, 236(1), pp. 100-112."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "GOUVEIA Luis"
]
2 => array:1 [
"name" => "LEITNER Markus"
]
]
"ouvrage" => ""
"keywords" => array:4 [
0 => "Integer programming"
1 => "OR in telecommunications"
2 => "Steiner tree"
3 => "Hop-constraints"
]
"updatedAt" => "2021-07-13 14:31:38"
"publicationUrl" => "https://doi.org/10.1016/j.ejor.2013.11.029"
"publicationInfo" => array:3 [
"pages" => "100-112"
"volume" => "236"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We consider a network design problem that generalizes the hop and diameter constrained Steiner tree problem as follows: Given an edge-weighted undirected graph with two disjoint subsets representing roots and terminals, find a minimum-weight subtree that spans all the roots and terminals so that the number of hops between each relevant node and an arbitrary root does not exceed a given hop limit H. The set of relevant nodes may be equal to the set of terminals, or to the union of terminals and root nodes. This article proposes integer linear programming models utilizing one layered graph for each root node. Different possibilities to relate solutions on each of the layered graphs as well as additional strengthening inequalities are then discussed. Furthermore, theoretical comparisons between these models and to previously proposed flow- and path-based formulations are given. To solve the problem to optimality, we implement branch-and-cut algorithms for the layered graph formulations. Our computational study shows their clear advantages over previously existing approaches."
"en" => "We consider a network design problem that generalizes the hop and diameter constrained Steiner tree problem as follows: Given an edge-weighted undirected graph with two disjoint subsets representing roots and terminals, find a minimum-weight subtree that spans all the roots and terminals so that the number of hops between each relevant node and an arbitrary root does not exceed a given hop limit H. The set of relevant nodes may be equal to the set of terminals, or to the union of terminals and root nodes. This article proposes integer linear programming models utilizing one layered graph for each root node. Different possibilities to relate solutions on each of the layered graphs as well as additional strengthening inequalities are then discussed. Furthermore, theoretical comparisons between these models and to previously proposed flow- and path-based formulations are given. To solve the problem to optimality, we implement branch-and-cut algorithms for the layered graph formulations. Our computational study shows their clear advantages over previously existing approaches."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
22 => Essec\Faculty\Model\Contribution {#2360
#_index: "academ_contributions"
#_id: "10565"
#_source: array:18 [
"id" => "10565"
"slug" => "the-bi-objective-prize-collecting-steiner-tree-problem"
"yearMonth" => "2014-12"
"year" => "2014"
"title" => "The bi-objective prize-collecting Steiner tree problem"
"description" => "LEITNER, M., LJUBIC, I. et SINNL, M. (2014). The bi-objective prize-collecting Steiner tree problem. <i>INFORMS Journal on Computing</i>, 27(1), pp. 118-134."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "LEITNER Markus"
]
2 => array:1 [
"name" => "SINNL Markus"
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "bi-objective combinatorial optimization"
1 => "Steiner tree problemϵ"
2 => "constraint method"
]
"updatedAt" => "2021-07-13 14:31:38"
"publicationUrl" => "https://doi.org/10.1016/j.endm.2013.05.091"
"publicationInfo" => array:3 [
"pages" => "118-134"
"volume" => "27"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In this paper, we study the bi-objective prize-collecting Steiner tree problem, whose goal is to find a subtree that minimizes the edge costs for building that tree, and, at the same time, to maximize the collected node revenues. We propose to solve the problem using an ϵ-constraint algorithm. This is an iterative mixed-integer-programming framework that identifies one solution for every point on the Pareto front. In this framework, a branch-and-cut approach for the single-objective variant of the problem is enhanced with warm-start procedures that are used to (i) generate feasible solutions, (ii) generate violated cutting planes, and (iii) guide the branching process. Standard benchmark instances from the literature are used to assess the efficacy of our method."
"en" => "In this paper, we study the bi-objective prize-collecting Steiner tree problem, whose goal is to find a subtree that minimizes the edge costs for building that tree, and, at the same time, to maximize the collected node revenues. We propose to solve the problem using an ϵ-constraint algorithm. This is an iterative mixed-integer-programming framework that identifies one solution for every point on the Pareto front. In this framework, a branch-and-cut approach for the single-objective variant of the problem is enhanced with warm-start procedures that are used to (i) generate feasible solutions, (ii) generate violated cutting planes, and (iii) guide the branching process. Standard benchmark instances from the literature are used to assess the efficacy of our method."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
23 => Essec\Faculty\Model\Contribution {#2361
#_index: "academ_contributions"
#_id: "10568"
#_source: array:18 [
"id" => "10568"
"slug" => "the-recoverable-robust-two-level-network-design-problem"
"yearMonth" => "2014-09"
"year" => "2014"
"title" => "The Recoverable Robust Two-Level Network Design Problem"
"description" => "ÁLVAREZ-MIRANDA, E., LJUBIC, I. et RAGHAVAN, S. (2014). The Recoverable Robust Two-Level Network Design Problem. <i>INFORMS Journal on Computing</i>, 27(1), pp. 1-19."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "ÁLVAREZ-MIRANDA Eduardo"
]
2 => array:1 [
"name" => "RAGHAVAN S."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-07-13 14:31:38"
"publicationUrl" => "https://doi.org/10.1287/ijoc.2014.0606"
"publicationInfo" => array:3 [
"pages" => "1-19"
"volume" => "27"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We consider a network design application that is modeled as the two-level network design problem under uncertainty. In this problem, one of the two available technologies can be installed on each edge and all customers of the network need to be served by at least the lower level (secondary) technology. The decision maker is confronted with uncertainty regarding the set of primary customers, i.e., the set of nodes that need to be served by the higher level (primary) technology. A set of discrete scenarios associated with the possible realizations of primary customers is available. The network is built in two stages. In the first stage the network topology must be determined. One may decide to install the primary technology on some of the edges in the first stage, or one can wait to see which scenario will be realized, in which case, edges with the installed secondary technology may be upgraded, if necessary to primary technology, but at higher recovery cost. The overall goal then is to build a “recoverable robust” spanning tree in the first stage that serves all customers by at least the lower level technology, and that minimizes the first-stage installation cost plus the worst-case cost needed to upgrade the edges of the selected tree, so that the primary customers of each scenario can be served using the primary technology. We discuss the complexity of the problem, provide mixed-integer programming models, and develop a branch-and-cut algorithm to solve it. Our extensive computational experiments demonstrate the efficacy of our approach."
"en" => "We consider a network design application that is modeled as the two-level network design problem under uncertainty. In this problem, one of the two available technologies can be installed on each edge and all customers of the network need to be served by at least the lower level (secondary) technology. The decision maker is confronted with uncertainty regarding the set of primary customers, i.e., the set of nodes that need to be served by the higher level (primary) technology. A set of discrete scenarios associated with the possible realizations of primary customers is available. The network is built in two stages. In the first stage the network topology must be determined. One may decide to install the primary technology on some of the edges in the first stage, or one can wait to see which scenario will be realized, in which case, edges with the installed secondary technology may be upgraded, if necessary to primary technology, but at higher recovery cost. The overall goal then is to build a “recoverable robust” spanning tree in the first stage that serves all customers by at least the lower level technology, and that minimizes the first-stage installation cost plus the worst-case cost needed to upgrade the edges of the selected tree, so that the primary customers of each scenario can be served using the primary technology. We discuss the complexity of the problem, provide mixed-integer programming models, and develop a branch-and-cut algorithm to solve it. Our extensive computational experiments demonstrate the efficacy of our approach."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
24 => Essec\Faculty\Model\Contribution {#2362
#_index: "academ_contributions"
#_id: "10615"
#_source: array:18 [
"id" => "10615"
"slug" => "the-generalized-regenerator-location-problem"
"yearMonth" => "2015-03"
"year" => "2015"
"title" => "The Generalized Regenerator Location Problem"
"description" => "CHEN, S., LJUBIC, I. et RAGHAVAN, S. (2015). The Generalized Regenerator Location Problem. <i>INFORMS Journal on Computing</i>, 27(2), pp. 204-220."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "CHEN Si"
]
2 => array:1 [
"name" => "RAGHAVAN S."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-07-13 14:31:39"
"publicationUrl" => "https://doi.org/10.1287/ijoc.2014.0621"
"publicationInfo" => array:3 [
"pages" => "204-220"
"volume" => "27"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In an optical network a signal can only travel a maximum distance dmax before its quality deteriorates to the point that it must be regenerated by installing regenerators at nodes of the network. As the cost of a regenerator is high, we wish to deploy as few regenerators as possible in the network, while ensuring all nodes can communicate with each other. In this paper we introduce the generalized regenerator location problem (GRLP) in which we are given a set S of nodes that corresponds to candidate locations for regenerators, and a set T of nodes that must communicate with each other. If S = T = N, we obtain the regenerator location problem (RLP), which we have studied previously and shown to be NP-complete. Our solution procedure to the RLP is based on its equivalence to the maximum leaf spanning tree problem (MLSTP). Unfortunately, this equivalence does not apply to the GRLP, nor do the procedures developed previously for the RLP. To solve the GRLP, we propose reduction procedures, two construction heuristics, and a local search procedure that we collectively refer to as a heuristic framework. We also establish a correspondence between the (node-weighted) directed Steiner forest problem and the GRLP. Using this fact, we provide several ways to derive natural and extended integer programming (IP) and mixed-integer programming (MIP) models for the GRLP and compare the strength of these models. Using the strongest model derived on the natural node selection variables we develop a branch-and-cut approach to solve the problem to optimality. The results indicate that the exact approach can easily solve instances with up to 200 nodes to optimality, whereas the heuristic framework is a high-quality approach for solving large-scale instances."
"en" => "In an optical network a signal can only travel a maximum distance dmax before its quality deteriorates to the point that it must be regenerated by installing regenerators at nodes of the network. As the cost of a regenerator is high, we wish to deploy as few regenerators as possible in the network, while ensuring all nodes can communicate with each other. In this paper we introduce the generalized regenerator location problem (GRLP) in which we are given a set S of nodes that corresponds to candidate locations for regenerators, and a set T of nodes that must communicate with each other. If S = T = N, we obtain the regenerator location problem (RLP), which we have studied previously and shown to be NP-complete. Our solution procedure to the RLP is based on its equivalence to the maximum leaf spanning tree problem (MLSTP). Unfortunately, this equivalence does not apply to the GRLP, nor do the procedures developed previously for the RLP. To solve the GRLP, we propose reduction procedures, two construction heuristics, and a local search procedure that we collectively refer to as a heuristic framework. We also establish a correspondence between the (node-weighted) directed Steiner forest problem and the GRLP. Using this fact, we provide several ways to derive natural and extended integer programming (IP) and mixed-integer programming (MIP) models for the GRLP and compare the strength of these models. Using the strongest model derived on the natural node selection variables we develop a branch-and-cut approach to solve the problem to optimality. The results indicate that the exact approach can easily solve instances with up to 200 nodes to optimality, whereas the heuristic framework is a high-quality approach for solving large-scale instances."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
25 => Essec\Faculty\Model\Contribution {#2363
#_index: "academ_contributions"
#_id: "10619"
#_source: array:18 [
"id" => "10619"
"slug" => "the-two-level-diameter-constrained-spanning-tree-problem"
"yearMonth" => "2015-04"
"year" => "2015"
"title" => "The Two-Level Diameter Constrained Spanning Tree Problem"
"description" => "GOUVEIA, L., LEITNER, M. et LJUBIC, I. (2015). The Two-Level Diameter Constrained Spanning Tree Problem. <i>Mathematical Programming</i>, 150(1), pp. 49-78."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "GOUVEIA Luis"
]
2 => array:1 [
"name" => "LEITNER Markus"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-07-13 14:31:39"
"publicationUrl" => "https://www.semanticscholar.org/paper/The-two-level-diameter-constrained-spanning-tree-Gouveia-Leitner/f5d267d43a2b0d4dce0226713ccbd3e3b2b5fb22"
"publicationInfo" => array:3 [
"pages" => "49-78"
"volume" => "150"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In this article, we introduce the two-level diameter constrained spanning tree problem (2-DMSTP), which generalizes the classical DMSTP by considering two sets of nodes with different latency requirements. We first observe that any feasible solution to the 2-DMSTP can be viewed as a DMST that contains a diameter constrained Steiner tree. This observation allows us to prove graph theoretical properties related to the centers of each tree which are then exploited to develop mixed integer programming formulations, valid inequalities, and symmetry breaking constraints. In particular, we propose a novel modeling approach based on a three-dimensional layered graph. In an extensive computational study we show that a branch-and-cut algorithm based on the latter model is highly effective in practice."
"en" => "In this article, we introduce the two-level diameter constrained spanning tree problem (2-DMSTP), which generalizes the classical DMSTP by considering two sets of nodes with different latency requirements. We first observe that any feasible solution to the 2-DMSTP can be viewed as a DMST that contains a diameter constrained Steiner tree. This observation allows us to prove graph theoretical properties related to the centers of each tree which are then exploited to develop mixed integer programming formulations, valid inequalities, and symmetry breaking constraints. In particular, we propose a novel modeling approach based on a three-dimensional layered graph. In an extensive computational study we show that a branch-and-cut algorithm based on the latter model is highly effective in practice."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
26 => Essec\Faculty\Model\Contribution {#2364
#_index: "academ_contributions"
#_id: "10636"
#_source: array:18 [
"id" => "10636"
"slug" => "intersection-cuts-for-bilevel-optimization"
"yearMonth" => "2016-05"
"year" => "2016"
"title" => "Intersection Cuts for Bilevel Optimization"
"description" => "FISCHETTI, M., LJUBIC, I., MONACI, M. et SINNL, M. (2016). Intersection Cuts for Bilevel Optimization. Dans: <i>Integer Programming and Combinatorial Optimization</i>. 1st ed. Berlin: Springer Computer Science, pp. 77-88."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "FISCHETTI Matteo"
]
2 => array:1 [
"name" => "MONACI Michele"
]
3 => array:1 [
"name" => "SINNL Markus"
]
]
"ouvrage" => "Integer Programming and Combinatorial Optimization"
"keywords" => array:3 [
0 => "Mixed Integer Programming"
1 => "Bilevel Optimization"
2 => "Stackelberg Games"
]
"updatedAt" => "2023-01-27 15:07:22"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "77-88"
"volume" => ""
"number" => ""
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
The exact solution of bilevel optimization problems is a very challenging task that received more and more attention in recent years, as witnessed by the flourishing recent literature on this topic. In this paper we present ideas and algorithms to solve to proven optimality generic Mixed-Integer Bilevel Linear Programs (MIBLP’s) where all constraints are linear, and some/all variables are required to take integer values.\n
In doing so, we look for a general-purpose approach applicable to any MIBLP (under mild conditions), rather than ad-hoc methods for specific cases. Our approach concentrates on minimal additions required to convert an effective branch-and-cut MILP exact code into a valid MIBLP solver, thus inheriting the wide arsenal of MILP tools (cuts, branching rules, heuristics) available in modern solvers.
"""
"en" => """
The exact solution of bilevel optimization problems is a very challenging task that received more and more attention in recent years, as witnessed by the flourishing recent literature on this topic. In this paper we present ideas and algorithms to solve to proven optimality generic Mixed-Integer Bilevel Linear Programs (MIBLP’s) where all constraints are linear, and some/all variables are required to take integer values.\n
In doing so, we look for a general-purpose approach applicable to any MIBLP (under mild conditions), rather than ad-hoc methods for specific cases. Our approach concentrates on minimal additions required to convert an effective branch-and-cut MILP exact code into a valid MIBLP solver, thus inheriting the wide arsenal of MILP tools (cuts, branching rules, heuristics) available in modern solvers.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
27 => Essec\Faculty\Model\Contribution {#2365
#_index: "academ_contributions"
#_id: "10643"
#_source: array:18 [
"id" => "10643"
"slug" => "operations-research-proceedings-2015"
"yearMonth" => "2016-07"
"year" => "2016"
"title" => "Operations Research Proceedings 2015"
"description" => "LJUBIC, I., DOERNER, K., TRAGLER, G. et PFLUG, G. [Eds] (2016). <i>Operations Research Proceedings 2015</i>. Springer."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "DOERNER Karl"
]
2 => array:1 [
"name" => "TRAGLER Gernot"
]
3 => array:1 [
"name" => "PFLUG Georg"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2023-01-27 15:06:47"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"type" => array:2 [
"fr" => "Direction d'ouvrage"
"en" => "Book editor"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
28 => Essec\Faculty\Model\Contribution {#2366
#_index: "academ_contributions"
#_id: "10720"
#_source: array:18 [
"id" => "10720"
"slug" => "a-new-bilevel-approach-for-the-k-vertex-cut-problem"
"yearMonth" => "2019-10"
"year" => "2019"
"title" => "A New Bilevel Approach for the K-vertex Cut Problem"
"description" => "FURINI, F., LJUBIC, I., MALAGUTI, E. et PARONUZZI, P. (2019). A New Bilevel Approach for the K-vertex Cut Problem. Dans: 2019 INFORMS Annual Meeting."
"authors" => array:4 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "FURINI Fabio"
]
2 => array:1 [
"name" => "MALAGUTI Enrico"
]
3 => array:1 [
"name" => "PARONUZZI Paolo"
]
]
"ouvrage" => "2019 INFORMS Annual Meeting"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-07-15T10:22:09.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.093916
+"parent": null
}
29 => Essec\Faculty\Model\Contribution {#2367
#_index: "academ_contributions"
#_id: "10846"
#_source: array:18 [
"id" => "10846"
"slug" => "une-methode-exacte-pour-le-probleme-dassortiment-optimal-avec-modele-de-choix-nested-logit"
"yearMonth" => "2020-02"
"year" => "2020"
"title" => "Une méthode exacte pour le problème d'assortiment optimal avec modèle de choix nested-logit"
"description" => "ALFANDARI, L., HASSANZADEH, A. et LJUBIC, I. (2020). Une méthode exacte pour le problème d'assortiment optimal avec modèle de choix nested-logit. Dans: 21st ROADEF 2020."
"authors" => array:3 [
0 => array:3 [
"name" => "ALFANDARI Laurent"
"bid" => "B00000901"
"slug" => "alfandari-laurent"
]
1 => array:3 [
"nam