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dc.contributor.authorAgárdi, Anita
dc.contributor.authorKovács, László
dc.contributor.authorBányai, Tamás
dc.date.accessioned2022-05-04T12:01:16Z
dc.date.available2022-05-04T12:01:16Z
dc.date.issued2021
dc.identifier.citationActa Polytechnica. 2021, vol. 61, no. 6, p. 672-683.
dc.identifier.issn1210-2709 (print)
dc.identifier.issn1805-2363 (online)
dc.identifier.urihttp://hdl.handle.net/10467/100614
dc.description.abstractThe Vehicle Routing Problem (VRP) is a highly researched discrete optimization task. The first article dealing with this problem was published by Dantzig and Ramster in 1959 under the name Truck Dispatching Problem. Since then, several versions of VRP have been developed. The task is NP difficult, it can be solved only in the foreseeable future, relying on different heuristic algorithms. The geometrical property of the state space influences the efficiency of the optimization method. In this paper, we present an analysis of the following state space methods: adaptive, reverse adaptive and uphill-downhill walk. In our paper, the efficiency of four operators are analysed on a complex Vehicle Routing Problem. These operators are the 2-opt, Partially Matched Crossover, Cycle Crossover and Order Crossover. Based on the test results, the 2-opt and Partially Matched Crossover are superior to the other two methods.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherČeské vysoké učení technické v Prazecs
dc.publisherCzech Technical University in Pragueen
dc.relation.ispartofseriesActa Polytechnica
dc.relation.urihttps://ojs.cvut.cz/ojs/index.php/ap/article/view/7291
dc.rightsCreative Commons Attribution 4.0 International Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleComparision of the walk techniques for fitness state space analysis in vehicle routing problem
dc.typearticleen
dc.date.updated2022-05-04T12:01:16Z
dc.identifier.doi10.14311/AP.2021.61.0672
dc.rights.accessopenAccess
dc.type.statusPeer-reviewed
dc.type.versionpublishedVersion


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Zobrazit minimální záznam

Creative Commons Attribution 4.0 International License
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