A new hybrid method based on Particle Swarm Optimization, Ant Colony Optimization and 3-Opt algorithms for Traveling Salesman Problem

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dc.contributor.authorMahi, Mostafa
dc.contributor.authorBaykan, Omer Kaan
dc.contributor.authorKodaz, Halife
dc.date.accessioned2020-03-26T19:00:27Z
dc.date.available2020-03-26T19:00:27Z
dc.date.issued2015
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThe Traveling Salesman Problem (TSP) is one of the standard test problems used in performance analysis of discrete optimization algorithms. The Ant Colony Optimization (ACO) algorithm appears among heuristic algorithms used for solving discrete optimization problems. In this study, a new hybrid method is proposed to optimize parameters that affect performance of the ACO algorithm using Particle Swarm Optimization (PSO). In addition, 3-Opt heuristic method is added to proposed method in order to improve local solutions. The PSO algorithm is used for detecting optimum values of parameters alpha and beta which are used for city selection operations in the ACO algorithm and determines significance of inter-city pheromone and distances. The 3-Opt algorithm is used for the purpose of improving city selection operations, which could not be improved due to falling in local minimums by the ACO algorithm. The performance of proposed hybrid method is investigated on ten different benchmark problems taken from literature and it is compared to the performance of some well-known algorithms. Experimental results show that the performance of proposed method by using fewer ants than the number of cities for the TSPs is better than the performance of compared methods in most cases in terms of solution quality and robustness. (C) 2015 Elsevier B.V. All rights reserved.en_US
dc.identifier.doi10.1016/j.asoc.2015.01.068en_US
dc.identifier.endpage490en_US
dc.identifier.issn1568-4946en_US
dc.identifier.issn1872-9681en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage484en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.asoc.2015.01.068
dc.identifier.urihttps://hdl.handle.net/20.500.12395/31774
dc.identifier.volume30en_US
dc.identifier.wosWOS:000351296200042en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherELSEVIER SCIENCE BVen_US
dc.relation.ispartofAPPLIED SOFT COMPUTINGen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectParticle Swarm Optimizationen_US
dc.subjectAnt Colony Optimizationen_US
dc.subject3-Opt algorithmen_US
dc.subjectTraveling Salesman Problemen_US
dc.titleA new hybrid method based on Particle Swarm Optimization, Ant Colony Optimization and 3-Opt algorithms for Traveling Salesman Problemen_US
dc.typeArticleen_US

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