Essec\Faculty\Model\Contribution {#2233
#_index: "academ_contributions"
#_id: "10921"
#_source: array:26 [
"id" => "10921"
"slug" => "the-incremental-connected-facility-location-problem"
"yearMonth" => "2019-12"
"year" => "2019"
"title" => "The Incremental Connected Facility Location Problem"
"description" => "ARULSELVAN, A., BLEY, A. et LJUBIC, I. (2019). The Incremental Connected Facility Location Problem. <i>Computers & Operations Research</i>, 112."
"authors" => array:3 [
0 => array:3 [
"name" => "LJUBIC Ivana"
"bid" => "B00683004"
"slug" => "ljubic-ivana"
]
1 => array:1 [
"name" => "ARULSELVAN Ashwin"
]
2 => array:1 [
"name" => "BLEY Andreas"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Mixed integer programming"
1 => "Facility location"
2 => "Branch-and-cut"
3 => "Multi-period network design"
4 => "Incremental network design"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://doi.org/10.1016/j.cor.2019.104763"
"publicationInfo" => array:3 [
"pages" => null
"volume" => "112"
"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 consider the incremental connected facility location problem (incremental ConFL), in which we are given a set of potential facilities, a set of interconnection nodes, a set of customers with demands, and a planning horizon. For each time period, we have to select a set of facilities to open, a set of customers to be served, the assignment of these customers to the open facilities, and a network that connects the open facilities. Once a customer is served, it must remain served in subsequent periods. Furthermore, in each time period the total demand of all customers served must be at least equal to a given minimum coverage requirement for that period. The objective is to minimize the total cost for building the network given by the investment and maintenance costs for the facilities and the network summed up over all time periods.\n
\n
We propose a mixed integer programming approach in which, in each time period, a single period ConFL with coverage restrictions has to be solved. For this latter problem, which is of particular interest in itself, new families of valid inequalities are proposed: these are set union knapsack cover (SUKC) inequalities, which are further enhanced by lifting and/or combined with cut-set inequalities, which are primarily used to ensure connectivity requirements. Details of an efficient branch-and-cut implementation are presented and computational results on a benchmark set of large instances are given, including examples of telecommunication networks in Germany.
"""
"en" => """
We consider the incremental connected facility location problem (incremental ConFL), in which we are given a set of potential facilities, a set of interconnection nodes, a set of customers with demands, and a planning horizon. For each time period, we have to select a set of facilities to open, a set of customers to be served, the assignment of these customers to the open facilities, and a network that connects the open facilities. Once a customer is served, it must remain served in subsequent periods. Furthermore, in each time period the total demand of all customers served must be at least equal to a given minimum coverage requirement for that period. The objective is to minimize the total cost for building the network given by the investment and maintenance costs for the facilities and the network summed up over all time periods.\n
\n
We propose a mixed integer programming approach in which, in each time period, a single period ConFL with coverage restrictions has to be solved. For this latter problem, which is of particular interest in itself, new families of valid inequalities are proposed: these are set union knapsack cover (SUKC) inequalities, which are further enhanced by lifting and/or combined with cut-set inequalities, which are primarily used to ensure connectivity requirements. Details of an efficient branch-and-cut implementation are presented and computational results on a benchmark set of large instances are given, including examples of telecommunication networks in Germany.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-21T13:21:44.000Z"
"docTitle" => "The Incremental Connected Facility Location Problem"
"docSurtitle" => "Articles"
"authorNames" => "<a href="/cv/ljubic-ivana">LJUBIC Ivana</a>, ARULSELVAN Ashwin, BLEY Andreas"
"docDescription" => "<span class="document-property-authors">LJUBIC Ivana, ARULSELVAN Ashwin, BLEY Andreas</span><br><span class="document-property-authors_fields">Systèmes d'Information, Data Analytics et Opérations</span> | <span class="document-property-year">2019</span>"
"keywordList" => "<a href="#">Mixed integer programming</a>, <a href="#">Facility location</a>, <a href="#">Branch-and-cut</a>, <a href="#">Multi-period network design</a>, <a href="#">Incremental network design</a>"
"docPreview" => "<b>The Incremental Connected Facility Location Problem</b><br><span>2019-12 | Articles </span>"
"docType" => "research"
"publicationLink" => "<a href="https://doi.org/10.1016/j.cor.2019.104763" target="_blank">The Incremental Connected Facility Location Problem</a>"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 8.760923
+"parent": null
}