A self-adaptive local search algorithm for the classical vehicle routing problem

dc.authorscopusid 24340715700
dc.authorscopusid 6602098044
dc.contributor.author Alabas-Uslu, Cigdem
dc.contributor.author Dengiz, Berna
dc.date.accessioned 2024-05-25T11:20:54Z
dc.date.available 2024-05-25T11:20:54Z
dc.date.issued 2011
dc.department Okan University en_US
dc.department-temp [Alabas-Uslu, Cigdem] TC Okan Univ, Dept Ind Engn, TR-34959 Istanbul, Turkey; [Dengiz, Berna] Baskent Univ, Dept Ind Engn, TR-06530 Ankara, Turkey en_US
dc.description.abstract The purpose of this study is introduction of a local search heuristic free from parameter tuning to solve classical vehicle routing problem (VRP). The VRP can be described as the problem of designing optimal delivery of routes from one depot to a number of customers under the limitations of side constraints to minimize the total traveling cost. The importance of this problem comes from practical as well as theoretical point of view. The proposed heuristic, self-adaptive local search (SALS), has one generic parameter which is learnt throughout the search process. Computational experiments confirm that SALS gives high qualified solutions to the VRP and ensures at least an average performance, in terms of efficiency and effectiveness, on the problem when compared with the recent and sophisticated approaches from the literature. The most important advantage of the proposed heuristic is the application convenience for the end-users. SALS also is flexible that can be easily applied to variations of VRP. (C) 2011 Elsevier Ltd. All rights reserved. en_US
dc.identifier.citationcount 29
dc.identifier.doi 10.1016/j.eswa.2011.01.116
dc.identifier.endpage 8998 en_US
dc.identifier.issn 0957-4174
dc.identifier.issn 1873-6793
dc.identifier.issue 7 en_US
dc.identifier.scopus 2-s2.0-79952442619
dc.identifier.scopusquality Q1
dc.identifier.startpage 8990 en_US
dc.identifier.uri https://doi.org/10.1016/j.eswa.2011.01.116
dc.identifier.uri https://hdl.handle.net/20.500.14517/543
dc.identifier.volume 38 en_US
dc.identifier.wos WOS:000289047700117
dc.identifier.wosquality Q1
dc.language.iso en
dc.publisher Pergamon-elsevier Science Ltd en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 34
dc.subject Vehicle routing en_US
dc.subject Metaheuristics en_US
dc.subject Parameter tuning en_US
dc.subject Self-adaptation en_US
dc.title A self-adaptive local search algorithm for the classical vehicle routing problem en_US
dc.type Article en_US
dc.wos.citedbyCount 25

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