Essec\Faculty\Model\Contribution {#2233
  #_index: "academ_contributions"
  #_id: "7876"
  #_source: array:26 [
    "id" => "7876"
    "slug" => "a-path-relinking-algorithm-for-the-generalized-assignement-problem"
    "yearMonth" => "2002-04"
    "year" => "2002"
    "title" => "A Path-relinking Algorithm for the Generalized Assignement Problem"
    "description" => "ALFANDARI, L., PLATEAU, A. et TOLLA, P. (2002). <i>A Path-relinking Algorithm for the Generalized Assignement Problem</i>. ESSEC Business School."
    "authors" => array:3 [
      0 => array:3 [
        "name" => "ALFANDARI Laurent"
        "bid" => "B00000901"
        "slug" => "alfandari-laurent"
      ]
      1 => array:1 [
        "name" => "PLATEAU A."
      ]
      2 => array:1 [
        "name" => "TOLLA P."
      ]
    ]
    "ouvrage" => ""
    "keywords" => []
    "updatedAt" => "2020-12-17 21:00:33"
    "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" => "Le Problème d'Affectation Généralisé (GAP) consiste à rechercher une affectation optimale de tâches à des agents soumis à des contraintes de capacité. Nous proposons un algorithme de Recomposition de Chemins (Path Relinking) pour ce problème, explorant à la fois l'espace des solutions réalisables et non réalisables. Les expériences numériques menées sur des instances de taille réduite de la OR-library illustrent l'efficacité de l'algorithme comparativement à la plupart des autres méthodes de la littérature. En particulier, les optima de plus de 95% des instances du fichier-test ont été trouvés en des temps de calcul relativement restreints."
      "en" => "The well-studied NP-hard Generalized Assignment Problem (GAP) consists in finding a maximum-profit assignment of tasks to agents such that each task is assigned to one agent and capacity constraints are satisfied for every agent. We propose a Path-Relinking heuristic for the GAPrelying on exploration of both feasible and infeasible solutions. Numerical experiments reported on small-size testbed instances of the OR-library show that the algorithm compares favorably to several other methods of the literature. In particular, more than 95% of the instances in the test-file were solved to optimality with short computation time."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-12-21T16:21:43.000Z"
    "docTitle" => "A Path-relinking Algorithm for the Generalized Assignement Problem"
    "docSurtitle" => "Documents de travail"
    "authorNames" => "<a href="/cv/alfandari-laurent">ALFANDARI Laurent</a>, PLATEAU A., TOLLA P."
    "docDescription" => "<span class="document-property-authors">ALFANDARI Laurent, PLATEAU A., TOLLA P.</span><br><span class="document-property-authors_fields">Systèmes d'Information, Data Analytics et Opérations</span> | <span class="document-property-year">2002</span>"
    "keywordList" => ""
    "docPreview" => "<b>A Path-relinking Algorithm for the Generalized Assignement Problem</b><br><span>2002-04 | Documents de travail </span>"
    "docType" => "research"
    "publicationLink" => "<a href="#" target="_blank">A Path-relinking Algorithm for the Generalized Assignement Problem</a>"
  ]
  +lang: "fr"
  +"_type": "_doc"
  +"_score": 8.758286
  +"parent": null
}