COMPARISON OF DIFFERENT CLUSTERING ALGORITHMS VIA GENETIC ALGORITHM FOR VRPTW

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dc.contributor.authorGocken, T.
dc.contributor.authorYaktubay, M.
dc.date.accessioned2025-01-06T17:44:48Z
dc.date.available2025-01-06T17:44:48Z
dc.date.issued2019
dc.description.abstractIn this paper, Vehicle Routing Problem with Time Windows (VRPTW) with known customer demands, a central depot and a set of vehicles with limited capacity, is considered. The objectives are both to minimize the total distance and the total waiting time of the vehicles while capacity and time windows constraints are secured. The applied solution techniques consist of three steps: clustering, routing and optimizing. By using K-means, Centroid-based heuristic, DBSCAN and SNN clustering algorithms in the initial population generation phase of genetic algorithm, the customers are divided into feasible clusters. Then feasible routes are constructed for each cluster. Lastly, the feasible route solutions are taken as the initial population and genetic algorithm is utilized for the optimization. A set of well-known benchmark data is used to compare the obtained results. According to the results of the study it is observed that using K-means clustering algorithm in generating the initial population of the genetic algorithm is more effective for the handled problem.
dc.identifier.doi10.2507/IJSIMM18(4)485
dc.identifier.endpage585
dc.identifier.issn1726-4529
dc.identifier.issn1996-8566
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85077609394
dc.identifier.scopusqualityQ1
dc.identifier.startpage574
dc.identifier.urihttps://doi.org/10.2507/IJSIMM18(4)485
dc.identifier.urihttps://hdl.handle.net/20.500.14669/3172
dc.identifier.volume18
dc.identifier.wosWOS:000500961000002
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherDaaam International Vienna
dc.relation.ispartofInternational Journal of Simulation Modelling
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectVehicle Routing with Time Windows
dc.subjectGenetic Algorithm
dc.subjectClustering
dc.subjectMulti-Objective Optimization
dc.subjectK-means Clustering Algorithm
dc.titleCOMPARISON OF DIFFERENT CLUSTERING ALGORITHMS VIA GENETIC ALGORITHM FOR VRPTW
dc.typeArticle

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