Essec\Faculty\Model\Contribution {#6196
  #_index: "academ_contributions"
  #_id: "13972"
  #_source: array:25 [
    "id" => "13972"
    "slug" => "the-generalized-close-enough-traveling-salesman-problem"
    "yearMonth" => "2023-05"
    "year" => "2023"
    "title" => "The generalized close enough traveling salesman problem"
    "description" => "DI PLACIDO, A., ARCHETTI, C., CERRONE, C. et GOLDEN, B. (2023). The generalized close enough traveling salesman problem. <i>European Journal of Operational Research</i>, In press."
    "authors" => array:4 [
      0 => array:3 [
        "name" => "ARCHETTI Claudia"
        "bid" => "B00773540"
        "slug" => "archetti-claudia"
      ]
      1 => array:1 [
        "name" => "DI PLACIDO Andrea"
      ]
      2 => array:1 [
        "name" => "CERRONE Carmine"
      ]
      3 => array:1 [
        "name" => "GOLDEN Bruce"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:4 [
      0 => "Metaheuristics"
      1 => "Close enough traveling salesman problem"
      2 => "Genetic algorithms"
      3 => "Conic programming"
    ]
    "updatedAt" => "2023-05-03 01:00:39"
    "publicationUrl" => "https://doi.org/10.1016/j.ejor.2023.04.010"
    "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" => "This paper studies a generalization of the close enough traveling salesman problem referred to as the generalized close enough traveling salesman problem (GCETSP). The canonical problem contains a set of customers, each associated with an area (neighborhood) that is generally circular. In the GCETSP, each customer is associated with a set of disks with different radii. Having multiple disks around the customer allows us to model several real-world applications, in which a higher benefit is gained by more closely approaching each target. A prize is assigned to each disk and is collected if the disk is traversed. The goal is to determine the route that visits each customer and the depot and maximizes the difference between the total collected prize and the route length. The total collected prize is given by the sum of the customer prices’ associated with the innermost disk traversed by the route. We propose a heuristic algorithm and an evolutionary approach, specifically, a genetic algorithm (GA), to solve this problem. We evaluate the GA’s performance on instances generated from benchmark CETSP and TSP instances. We then compare GA solutions with CETSP solutions and solutions obtained through an alternative approach based on pre-selecting intersection points with customers’ disks. The results show that the GA can identify high-quality solutions with a short computing time."
      "en" => "This paper studies a generalization of the close enough traveling salesman problem referred to as the generalized close enough traveling salesman problem (GCETSP). The canonical problem contains a set of customers, each associated with an area (neighborhood) that is generally circular. In the GCETSP, each customer is associated with a set of disks with different radii. Having multiple disks around the customer allows us to model several real-world applications, in which a higher benefit is gained by more closely approaching each target. A prize is assigned to each disk and is collected if the disk is traversed. The goal is to determine the route that visits each customer and the depot and maximizes the difference between the total collected prize and the route length. The total collected prize is given by the sum of the customer prices’ associated with the innermost disk traversed by the route. We propose a heuristic algorithm and an evolutionary approach, specifically, a genetic algorithm (GA), to solve this problem. We evaluate the GA’s performance on instances generated from benchmark CETSP and TSP instances. We then compare GA solutions with CETSP solutions and solutions obtained through an alternative approach based on pre-selecting intersection points with customers’ disks. The results show that the GA can identify high-quality solutions with a short computing time."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
      "en" => "Information Systems, Decision Sciences and Statistics"
    ]
    "indexedAt" => "2023-12-10T23:22:14.000Z"
    "docTitle" => "The generalized close enough traveling salesman problem"
    "docSurtitle" => "Articles"
    "authorNames" => "<a href="/cv/archetti-claudia">ARCHETTI Claudia</a>, DI PLACIDO Andrea, CERRONE Carmine, GOLDEN Bruce"
    "docDescription" => "<span class="document-property-authors">ARCHETTI Claudia, DI PLACIDO Andrea, CERRONE Carmine, GOLDEN Bruce</span><br><span class="document-property-authors_fields">Systèmes d’Information, Sciences de la Décision et Statistiques</span> | <span class="document-property-year">2023</span>"
    "keywordList" => "<a href="#">Metaheuristics</a>, <a href="#">Close enough traveling salesman problem</a>, <a href="#">Genetic algorithms</a>, <a href="#">Conic programming</a>"
    "docPreview" => "<b>The generalized close enough traveling salesman problem</b><br><span>2023-05 | Articles </span>"
    "docType" => "research"
  ]
  +lang: "fr"
  +"_type": "_doc"
  +"_score": 8.847877
  +"parent": null
}