A symbiotic organisms search algorithm-based design optimization of constrained multi-objective engineering design problems

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dc.authoridhttps://orcid.org/0000-0002-7687-9061
dc.authoridhttps://orcid.org/0000-0002-5229-4018
dc.authoridhttps://orcid.org/0000-0002-3612-0640
dc.authorscopusid36728602600
dc.authorwosidG-2829-2015
dc.authorwosidAAH-9889-2020
dc.authorwosidD-7354-2015
dc.contributor.authorÜstün, Deniz
dc.contributor.authorCarbas, Serdar
dc.contributor.authorToktaş, Abdurrahim
dc.date.accessioned2024-08-02T13:26:59Z
dc.date.available2024-08-02T13:26:59Z
dc.date.issued2021
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractPurpose In line with computational technological advances, obtaining optimal solutions for engineering problems has become attractive research topics in various disciplines and real engineering systems having multiple objectives. Therefore, it is aimed to ensure that the multiple objectives are simultaneously optimized by considering them among the trade-offs. Furthermore, the practical means of solving those problems are principally concentrated on handling various complicated constraints. The purpose of this paper is to suggest an algorithm based on symbiotic organisms search (SOS), which mimics the symbiotic reciprocal influence scheme adopted by organisms to live on and breed within the ecosystem, for constrained multi-objective engineering design problems. Design/methodology/approach Though the general performance of SOS algorithm was previously well demonstrated for ordinary single objective optimization problems, its efficacy on multi-objective real engineering problems will be decisive about the performance. The SOS algorithm is, hence, implemented to obtain the optimal solutions of challengingly constrained multi-objective engineering design problems using the Pareto optimality concept. Findings Four well-known mixed constrained multi-objective engineering design problems and a real-world complex constrained multilayer dielectric filter design problem are tackled to demonstrate the precision and stability of the multi-objective SOS (MOSOS) algorithm. Also, the comparison of the obtained results with some other well-known metaheuristics illustrates the validity and robustness of the proposed algorithm. Originality/value The algorithmic performance of the MOSOS on the challengingly constrained multi-objective multidisciplinary engineering design problems with constraint-handling approach is successfully demonstrated with respect to the obtained outperforming final optimal designs.
dc.identifier.citationUstun, D., Carbas, S. and Toktas, A. (2021). A symbiotic organisms search algorithm-based design optimization of constrained multi-objective engineering design problems. Engineering Computations, 38 (2), 632-658. https://doi.org/10.1108/EC-03-2020-0140
dc.identifier.doi10.1108/EC-03-2020-0140
dc.identifier.endpage658en_US
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85087632968
dc.identifier.startpage632en_US
dc.identifier.urihttps://doi.org/10.1108/EC-03-2020-0140
dc.identifier.urihttps://hdl.handle.net/20.500.13099/325
dc.identifier.volume38en_US
dc.identifier.wosWOS:000547835700001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.institutionauthorÜstün, Deniz
dc.language.isoen
dc.publisherEmerald Insight
dc.relation.ispartofEngineering Computations
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectMulti-objective optimization
dc.subjectPareto optimality
dc.subjectConstrained engineering design problems
dc.subjectMultilayer dielectric filter
dc.subjectOptimum design
dc.subjectSymbiotic organisms search algorithm
dc.titleA symbiotic organisms search algorithm-based design optimization of constrained multi-objective engineering design problems
dc.typeArticle

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