Essec\Faculty\Model\Contribution {#2233
#_index: "academ_contributions"
#_id: "718"
#_source: array:26 [
"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, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-12-26T09:21:48.000Z"
"docTitle" => "Benders Decomposition without Separability: A Computational Study for Capacitated Facility Location Problems"
"docSurtitle" => "Articles"
"authorNames" => "<a href="/cv/ljubic-ivana">LJUBIC Ivana</a>, FICHETTI M., SINNL M."
"docDescription" => "<span class="document-property-authors">LJUBIC Ivana, FICHETTI M., SINNL M.</span><br><span class="document-property-authors_fields">Systèmes d'Information, Data Analytics et Opérations</span> | <span class="document-property-year">2016</span>"
"keywordList" => "<a href="#">Benders decomposition</a>, <a href="#">Congested capacitated facility location</a>, <a href="#">Perspective reformulation</a>, <a href="#">Branch-and-cut</a>, <a href="#">Mixed-integer convex programming</a>"
"docPreview" => "<b>Benders Decomposition without Separability: A Computational Study for Capacitated Facility Location Problems</b><br><span>2016-09 | Articles </span>"
"docType" => "research"
"publicationLink" => "<a href="https://www.sciencedirect.com/science/article/abs/pii/S0377221716301126" target="_blank">Benders Decomposition without Separability: A Computational Study for Capacitated Facility Location Problems</a>"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 8.957939
+"parent": null
}
