A COMPARATIVE STUDY ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHMS FOR TRAVELING SALESMAN PROBLEMS

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dc.contributor.authorCunkas, Mehmet
dc.contributor.authorOzsaglam, M. Yasin
dc.date.accessioned2020-03-26T17:37:42Z
dc.date.available2020-03-26T17:37:42Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis article deals with a performance evaluation of particle swarm optimization (PSO) and genetic algorithms (GA) for traveling salesman problem (TSP). This problem is known to be NP-hard, and consists of the solution containing N! permutations. The objective of the study is to compare the ability to solve the large-scale and other benchmark problems for both algorithms. All simulation has been performed using a software program developed in the Delphi environment. As yet, overall results show that genetic algorithms generally can find better solutions compared to the PSO algorithm, but in terms of average generation it is not good enough.en_US
dc.identifier.doi10.1080/01969720903068435en_US
dc.identifier.endpage507en_US
dc.identifier.issn0196-9722en_US
dc.identifier.issn1087-6553en_US
dc.identifier.issue6en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage490en_US
dc.identifier.urihttps://dx.doi.org/10.1080/01969720903068435
dc.identifier.urihttps://hdl.handle.net/20.500.12395/23201
dc.identifier.volume40en_US
dc.identifier.wosWOS:000268191100002en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTAYLOR & FRANCIS INCen_US
dc.relation.ispartofCYBERNETICS AND SYSTEMSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectGenetic algorithmsen_US
dc.subjectParticle swarm optimizationen_US
dc.subjectTraveling salesman problemen_US
dc.titleA COMPARATIVE STUDY ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHMS FOR TRAVELING SALESMAN PROBLEMSen_US
dc.typeArticleen_US

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