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

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dc.authoridhttps://orcid.org/0000-0002-7687-9061en_US
dc.authoridhttps://orcid.org/0000-0002-5229-4018en_US
dc.authoridhttps://orcid.org/0000-0002-3612-0640en_US
dc.authorscopusid36728602600en_US
dc.authorwosidG-2829-2015en_US
dc.authorwosidAAH-9889-2020en_US
dc.authorwosidD-7354-2015en_US
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.issued2021en_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
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.en_US
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-03-2020-0140en_US
dc.identifier.doi10.1108/EC-03-2020-0140en_US
dc.identifier.endpage658en_US
dc.identifier.issue2en_US
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.wos000547835700001en_US
dc.identifier.wosqualityQ3en_US
dc.institutionauthorÜstün, Deniz
dc.language.isoengen_US
dc.publisherEmerald Insighten_US
dc.relation.ispartofEngineering Computationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_US
dc.subjectMulti-objective optimizationen_US
dc.subjectPareto optimalityen_US
dc.subjectConstrained engineering design problemsen_US
dc.subjectMultilayer dielectric filteren_US
dc.subjectOptimum designen_US
dc.subjectSymbiotic organisms search algorithmen_US
dc.titleA symbiotic organisms search algorithm-based design optimization of constrained multi-objective engineering design problemsen_US
dc.typearticleen_US

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