An artificial algae algorithm for solving binary optimization problems

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dc.contributor.authorKorkmaz, Sedat
dc.contributor.authorBabalik, Ahmet
dc.contributor.authorKiran, Mustafa Servet
dc.date.accessioned2020-03-26T19:52:50Z
dc.date.available2020-03-26T19:52:50Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis paper focuses on modification of basic artificial algae algorithm (AAA) for solving binary optimization problems by using a new solution update rule because the agents in AAA work on continuous solution space. The candidate solution generation process of algorithm in the basic version of AAA is replaced with a mechanism that use a neighbor solution randomly selected from the population and three decision variables of this solution. The current solution is taken from the population and randomly selected three dimensions of this solution are changed using the neighbor solution. The agents of AAA work on continuous solution space and this modification for AAA is required for solving a binary optimization problem because a binary optimization problems have decision variables which are element of set {0, 1}. The performance of the proposed algorithm, binAAA for short, is investigated on the uncapacitated facility location problems which are pure binary optimization problem and there is no integer or real valued decision variables in this problem. The results obtained by binAAA are compared with the results of state-of-art algorithms such as artificial bee colony, particle swarm optimization, and genetic algorithms. Experimental results and comparisons show that the binAAA is better than the other algorithm almost all cases in terms of solution quality and robustness based on the mean and standard deviations, respectively.en_US
dc.identifier.doi10.1007/s13042-017-0772-7en_US
dc.identifier.endpage1247en_US
dc.identifier.issn1868-8071en_US
dc.identifier.issn1868-808Xen_US
dc.identifier.issue7en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1233en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s13042-017-0772-7
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36309
dc.identifier.volume9en_US
dc.identifier.wosWOS:000436014500013en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGER HEIDELBERGen_US
dc.relation.ispartofINTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectArtificial algae algorithmen_US
dc.subjectBinary optimizationen_US
dc.subjectHeuristic searchen_US
dc.subjectUncapacitated facility locationen_US
dc.titleAn artificial algae algorithm for solving binary optimization problemsen_US
dc.typeArticleen_US

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