A recombination-based hybridization of particle swarm optimization and artificial bee colony algorithm for continuous optimization problems

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dc.contributor.authorKiran, Mustafa Servet
dc.contributor.authorGunduz, Mesut
dc.date.accessioned2020-03-26T18:41:03Z
dc.date.available2020-03-26T18:41:03Z
dc.date.issued2013
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis paper presents a hybridization of particle swarm optimization (PSO) and artificial bee colony (ABC) approaches, based on recombination procedure. The PSO and ABC are population-based iterative methods. While the PSO directly uses the global best solution of the population to determine new positions for the particles at the each iteration, agents (employed, onlooker and scout bees) of the ABC do not directly use this information but the global best solution in the ABC is stored at the each iteration. The global best solutions obtained by the PSO and ABC are used for recombination, and the solution obtained from this recombination is given to the populations of the PSO and ABC as the global best and neighbor food source for onlooker bees, respectively. Information flow between particle swarm and bee colony helps increase global and local search abilities of the hybrid approach which is referred to as Hybrid approach based on Particle swarm optimization and Artificial bee colony algorithm, HPA for short. In order to test the performance of the HPA algorithm, this study utilizes twelve basic numerical benchmark functions in addition to CEC2005 composite functions and an energy demand estimation problem. The experimental results obtained by the HPA are compared with those of the PSO and ABC. The performance of the HPA is also compared with that of other hybrid methods based on the PSO and ABC. The experimental results show that the HPA algorithm is an alternative and competitive optimizer for continuous optimization problems. (C) 2012 Elsevier B.V. All rights reserved.en_US
dc.identifier.doi10.1016/j.asoc.2012.12.007en_US
dc.identifier.endpage2203en_US
dc.identifier.issn1568-4946en_US
dc.identifier.issn1872-9681en_US
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2188en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.asoc.2012.12.007
dc.identifier.urihttps://hdl.handle.net/20.500.12395/29185
dc.identifier.volume13en_US
dc.identifier.wosWOS:000316767100055en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherELSEVIERen_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.subjectArtificial bee colonyen_US
dc.subjectParticle swarm optimizationen_US
dc.subjectRecombination procedureen_US
dc.subjectHybridizationen_US
dc.subjectContinuous optimizationen_US
dc.titleA recombination-based hybridization of particle swarm optimization and artificial bee colony algorithm for continuous optimization problemsen_US
dc.typeArticleen_US

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