Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "15382"
  #_source: array:26 [
    "id" => "15382"
    "slug" => "last-fifty-years-of-integer-linear-programming-a-focus-on-recent-practical-advances"
    "yearMonth" => "2024-11"
    "year" => "2024"
    "title" => "Last fifty years of integer linear programming: A focus on recent practical advances"
    "description" => "CLAUTIAUX, F. et LJUBIC, I. (2024). Last fifty years of integer linear programming: A focus on recent practical advances. <i>European Journal of Operational Research</i>, In press."
    "authors" => array:2 [
      0 => array:3 [
        "name" => "LJUBIC Ivana"
        "bid" => "B00683004"
        "slug" => "ljubic-ivana"
      ]
      1 => array:1 [
        "name" => "Clautiaux François"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:5 [
      0 => "Combinatorial optimization"
      1 => "Mixed-integer linear programming"
      2 => "Branch-and-cut"
      3 => "Dantzig–Wolfe decomposition"
      4 => "Benders decomposition"
    ]
    "updatedAt" => "2024-12-10 01:00:51"
    "publicationUrl" => "https://doi.org/10.1016/j.ejor.2024.11.018"
    "publicationInfo" => array:3 [
      "pages" => ""
      "volume" => "In press"
      "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" => """
        Mixed-integer linear programming (MILP) has become a cornerstone of operations research. This is driven by the enhanced efficiency of modern solvers, which can today find globally optimal solutions within seconds for problems that were out of reach a decade ago. The versatility of these solvers allowed successful applications in many areas, such as transportation, logistics, supply chain management, revenue management, finance, telecommunications, and manufacturing. Despite the impressive success already obtained, many challenges remain, and MILP is still a very active field.\n
        This article provides an overview of the most significant results achieved in advancing the MILP solution methods. Given the immense literature on this topic, we made deliberate choices to focus on computational aspects and recent practical performance improvements, emphasizing research that reports computational experiments. We organize our survey into three main parts, dedicated to branch-and-cut methods, Dantzig–Wolfe decomposition, and Benders decomposition. The paper concludes by highlighting ongoing challenges and future opportunities in MILP research.
        """
      "en" => """
        Mixed-integer linear programming (MILP) has become a cornerstone of operations research. This is driven by the enhanced efficiency of modern solvers, which can today find globally optimal solutions within seconds for problems that were out of reach a decade ago. The versatility of these solvers allowed successful applications in many areas, such as transportation, logistics, supply chain management, revenue management, finance, telecommunications, and manufacturing. Despite the impressive success already obtained, many challenges remain, and MILP is still a very active field.\n
        This article provides an overview of the most significant results achieved in advancing the MILP solution methods. Given the immense literature on this topic, we made deliberate choices to focus on computational aspects and recent practical performance improvements, emphasizing research that reports computational experiments. We organize our survey into three main parts, dedicated to branch-and-cut methods, Dantzig–Wolfe decomposition, and Benders decomposition. The paper concludes by highlighting ongoing challenges and future opportunities in MILP research.
        """
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-12-30T17:21:46.000Z"
    "docTitle" => "Last fifty years of integer linear programming: A focus on recent practical advances"
    "docSurtitle" => "Journal articles"
    "authorNames" => "<a href="/cv/ljubic-ivana">LJUBIC Ivana</a>, Clautiaux François"
    "docDescription" => "<span class="document-property-authors">LJUBIC Ivana, Clautiaux François</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2024</span>"
    "keywordList" => "<a href="#">Combinatorial optimization</a>, <a href="#">Mixed-integer linear programming</a>, <a href="#">Branch-and-cut</a>, <a href="#">Dantzig–Wolfe decomposition</a>, <a href="#">Benders decomposition</a>"
    "docPreview" => "<b>Last fifty years of integer linear programming: A focus on recent practical advances</b><br><span>2024-11 | Journal articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://doi.org/10.1016/j.ejor.2024.11.018" target="_blank">Last fifty years of integer linear programming: A focus on recent practical advances</a>"
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 8.957939
  +"parent": null
}