Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/236
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dc.contributor.authorBaş, Emine-
dc.contributor.authorÜlker, Erkan-
dc.date.accessioned2021-12-13T10:23:54Z-
dc.date.available2021-12-13T10:23:54Z-
dc.date.issued2020-
dc.identifier.issn1432-7643-
dc.identifier.issn1433-7479-
dc.identifier.urihttps://doi.org/10.1007/s00500-020-04718-w-
dc.identifier.urihttps://hdl.handle.net/20.500.13091/236-
dc.description.abstractThe social spider algorithm (SSA) is a new heuristic algorithm created on spider behaviors. The original study of this algorithm was proposed to solve continuous problems. In this paper, the binary version of SSA (binary SSA) is introduced to solve binary problems. Currently, there is insufficient focus on the binary version of SSA in the literature. The main part of the binary version is at the transfer function. The transfer function is responsible for mapping continuous search space to discrete search space. In this study, four of the transfer functions divided into two families, S-shaped and V-shaped, are evaluated. Thus, four different variations of binary SSA are formed as binary SSA-Tanh, binary SSA-Sigm, binary SSA-MSigm and binary SSA-Arctan. Two different techniques (SimSSA and LogicSSA) are developed at the candidate solution production schema in binary SSA. SimSSA is used to measure similarities between two binary solutions. With SimSSA, binary SSA's ability to discover new points in search space has been increased. Thus, binary SSA is able to find global optimum instead of local optimums. LogicSSA which is inspired by the logic gates and a popular method in recent years has been used to avoid local minima traps. By these two techniques, the exploration and exploitation capabilities of binary SSA in the binary search space are improved. Eighteen unimodal and multimodal standard benchmark optimization functions are employed to evaluate variations of binary SSA. To select the best variations of binary SSA, a comparative study is presented. The Wilcoxon signed-rank test has applied to the experimental results of variations of binary SSA. Compared to well-known evolutionary and recently developed methods in the literature, the variations of binary SSA performance is quite good. In particular, binary SSA-Tanh and binary SSA-Arctan variations of binary SSA showed superior performance.en_US
dc.language.isoenen_US
dc.publisherSPRINGERen_US
dc.relation.ispartofSOFT COMPUTINGen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBinary Optimizationen_US
dc.subjectSocial Spider Algorithmen_US
dc.subjectTransfer Functionen_US
dc.subjectParticle Swarm Optimizationen_US
dc.subjectSelectionen_US
dc.subjectIntelligenceen_US
dc.titleA binary social spider algorithm for continuous optimization tasken_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s00500-020-04718-w-
dc.identifier.scopus2-s2.0-85078840510en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.authoridUlker, Erkan/0000-0003-4393-9870-
dc.authorwosidUlker, Erkan/ABA-5846-2020-
dc.identifier.volume24en_US
dc.identifier.issue17en_US
dc.identifier.startpage12953en_US
dc.identifier.endpage12979en_US
dc.identifier.wosWOS:000510297200001en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.authorscopusid57213265310-
dc.authorscopusid23393979800-
dc.identifier.scopusqualityQ2-
item.openairetypeArticle-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextembargo_20300101-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.dept02.03. Department of Computer Engineering-
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections
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