Improvement of a genetic algorithm approach for the solution of vehicle routing problem with time windows

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dc.contributor.authorGöçken, Tolunay
dc.contributor.authorYaktubay, Meltem
dc.contributor.authorKiliç, Fatih
dc.date.accessioned2025-01-06T17:29:43Z
dc.date.available2025-01-06T17:29:43Z
dc.date.issued2017
dc.description2017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017 -- 16 September 2017 through 17 September 2017 -- Malatya -- 115012
dc.description.abstractIn this study, Vehicle Routing Problem with Time Windows (VRPTW) with known customer demands, a single depot and identical vehicles, is considered. Minimizing the total distance and the total waiting time of the vehicles are determined as objective functions for VRPTW which is capable to serve the customers in a prespecified time interval. A hybridized version of genetic algorithm which is a metaheuristic solution technique with constructive heuristic methods is proposed to produce effective solutions for VRPTW. By using sweep algorithm in initial population generation phase of genetic algorithm, it is planned to begin the search with high quality solution sets and in this way, get more feasible solutions faster. A benchmark problem in the literature is solved and obtained results are compared with the results of genetic algorithm with the nearest neighbor algorithm based algorithm. It is observed that the proposed genetic algorithm beginning with sweep based initial population generation algorithm reaches more effective solutions. © 2017 IEEE.
dc.description.sponsorshipAdana Science and Technology University
dc.identifier.doi10.1109/IDAP.2017.8090185
dc.identifier.isbn978-153861880-6
dc.identifier.scopus2-s2.0-85039922765
dc.identifier.urihttps://doi.org/10.1109/IDAP.2017.8090185
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1303
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofIDAP 2017 - International Artificial Intelligence and Data Processing Symposium
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectGenetic algorithm
dc.subjectMulti-objective optimization
dc.subjectNSGA-II
dc.subjectSweep algorithm
dc.subjectVehicle routing
dc.titleImprovement of a genetic algorithm approach for the solution of vehicle routing problem with time windows
dc.typeConference Object

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