Essec\Faculty\Model\Contribution {#2190`
#_index: "academ_contributions"
#_id: "12121"
#_source: array:26 [``
"id" => "12121"
"slug" => "ants-can-solve-the-team-orienteering-problem"
"yearMonth" => "2008-01"
"year" => "2008"
"title" => "Ants can solve the team orienteering problem"
"description" => "KE, L., ARCHETTI, C. et FENG, Z. (2008). Ants can solve the team orienteering problem. <i>Computers & Industrial Engineering</i>, 54(3), pp. 648-665."
"authors" => array:3 [``
0 => array:3 [``
"name" => "ARCHETTI Claudia"
"bid" => "B00773540"
"slug" => "archetti-claudia"
`]
1 => array:1 [`
"name" => "KE Liangjun"
`]
2 => array:1 [`
"name" => "FENG Zuren"
`]
]
"ouvrage" => ""
"keywords" => array:4 [`
0 => "Team orienteering problem"
1 => "Ant colony optimization"
2 => "Ant system"
3 => "Heuristics"
`]
"updatedAt" => "2021-07-13 14:32:00"
"publicationUrl" => "https://doi.org/10.1016/j.cie.2007.10.001"
"publicationInfo" => array:3 [`
"pages" => "648-665"
"volume" => "54"
"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 team orienteering problem (TOP) involves finding a set of paths from the starting point to the ending point such that the total collected reward received from visiting a subset of locations is maximized and the length of each path is restricted by a pre-specified limit. In this paper, an ant colony optimization (ACO) approach is proposed for the team orienteering problem. Four methods, i.e., the sequential, deterministic-concurrent and random-concurrent and simultaneous methods, are proposed to construct candidate solutions in the framework of ACO. We compare these methods according to the results obtained on well-known problems from the literature. Finally, we compare the algorithm with several existing algorithms. The results show that our algorithm is promising."
"en" => "The team orienteering problem (TOP) involves finding a set of paths from the starting point to the ending point such that the total collected reward received from visiting a subset of locations is maximized and the length of each path is restricted by a pre-specified limit. In this paper, an ant colony optimization (ACO) approach is proposed for the team orienteering problem. Four methods, i.e., the sequential, deterministic-concurrent and random-concurrent and simultaneous methods, are proposed to construct candidate solutions in the framework of ACO. We compare these methods according to the results obtained on well-known problems from the literature. Finally, we compare the algorithm with several existing algorithms. The results show that our algorithm is promising."
`]
"authors_fields" => array:2 [`
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
`]
"indexedAt" => "2024-04-16T13:22:00.000Z"
"docTitle" => "Ants can solve the team orienteering problem"
"docSurtitle" => "Journal articles"
"authorNames" => "<a href="/cv/archetti-claudia">ARCHETTI Claudia</a>, KE Liangjun, FENG Zuren"
"docDescription" => "<span class="document-property-authors">ARCHETTI Claudia, KE Liangjun, FENG Zuren</span><br><span class="document-property-authors_fields">Information Systems, Decision Sciences and Statistics</span> | <span class="document-property-year">2008</span>"
"keywordList" => "<a href="#">Team orienteering problem</a>, <a href="#">Ant colony optimization</a>, <a href="#">Ant system</a>, <a href="#">Heuristics</a>"
"docPreview" => "<b>Ants can solve the team orienteering problem</b><br><span>2008-01 | Journal articles </span>"
"docType" => "research"
"publicationLink" => "<a href="https://doi.org/10.1016/j.cie.2007.10.001" target="_blank">Ants can solve the team orienteering problem</a>"
]
+lang: "en"
+"_type": "_doc"
+"_score": 8.776598
+"parent": null
}