An improvement in fruit fly optimization algorithm by using sign parameters

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dc.contributor.authorBabalik, Ahmet
dc.contributor.authorIscan, Hazim
dc.contributor.authorBabaoglu, Ismail
dc.contributor.authorGunduz, Mesut
dc.date.accessioned2020-03-26T19:52:52Z
dc.date.available2020-03-26T19:52:52Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThe fruit fly optimization algorithm (FOA) has been developed by inspiring osphresis and vision behaviors of the fruit flies to solve continuous optimization problems. As many researchers know that FOA has some shortcomings, this study presents an improved version of FOA to remove with these shortcomings in order to improve its optimization performance. According to the basic version of FOA, the candidate solutions could not take values those are negative as well as stated in many studies in the literature. In this study, two sign parameters are added into the original FOA to consider not only the positive side of the search space, but also the whole. To experimentally validate the proposed approach, namely signed FOA, SFOA for short, 21 well-known benchmark problems are considered. In order to demonstrate the effectiveness and success of the proposed method, the results of the proposed approach are compared with the results of the original FOA, results of the two different state-of-art versions of particle swarm optimization algorithm, results of the cuckoo search optimization algorithm and results of the firefly optimization algorithm. By analyzing experimental results, it can be said that the proposed approach achieves more successful results on many benchmark problems than the compared methods, and SFOA is presented as more equal and fairer in terms of screening the solution space.en_US
dc.identifier.doi10.1007/s00500-017-2733-1en_US
dc.identifier.endpage7603en_US
dc.identifier.issn1432-7643en_US
dc.identifier.issn1433-7479en_US
dc.identifier.issue22en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage7587en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s00500-017-2733-1
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36322
dc.identifier.volume22en_US
dc.identifier.wosWOS:000448418300021en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGERen_US
dc.relation.ispartofSOFT COMPUTINGen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectSwarm intelligenceen_US
dc.subjectContinuous optimizationen_US
dc.subjectSigned fruit fly optimization algorithmen_US
dc.subjectBenchmark functionen_US
dc.titleAn improvement in fruit fly optimization algorithm by using sign parametersen_US
dc.typeArticleen_US

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