Diversity enhanced Equilibrium Optimization algorithm for solving unconstrained and constrained optimization problems

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dc.contributor.authorTurgut, Oguz Emrah
dc.contributor.authorTurgut, Mert Sinan
dc.date.accessioned2024-03-09T18:48:16Z
dc.date.available2024-03-09T18:48:16Z
dc.date.issued2023
dc.departmentİzmir Bakırçay Üniversitesien_US
dc.description.abstractThis research study proposes a novel mutation scheme mainly based on the manipulation equations of Tangent Search Optimization and mutualism phase of Symbiotic Organism Search algorithms to be implemented on the Equilibrium Optimization algorithm to enhance the solution diversity among the population individuals. Beneficial coordination between these governing search mechanisms enables maintaining diversity in the population. It eliminates the stagnation towards the local sub-optimal solutions over the search domain, significantly alleviating the inherent drawbacks of Equilibrium Optimizer. To assess the efficiency of the proposed diversity-enhanced Equilibrium Optimization algorithm (DEQUIL) on unconstrained problems, thirty-four multidimensional optimization test instances comprised of unimodal and multimodal benchmark problems have been solved, and respective performances are verified against those obtained from well-reputed new emerged metaheuristic algorithms. A comprehensive comparison based on the decisive metrics, including statistical analysis, performance index analysis, scalability tests, diversity analysis, and convergence rates demonstrates the effectiveness of the hybrid search methodology. Later, fourteen real-world constrained engineering problems with varying complexities were solved by the proposed DEQUIL method. The prediction performance of DEQUIL is compared with a wide range of available literature optimizers to scrutinize the improvements in problem-solving capabilities and seen that it can successfully cope with the complex constrained design problems outperforming the majority of the compared algorithm in most design cases.en_US
dc.identifier.doi10.1007/s12065-023-00877-5
dc.identifier.issn1864-5909
dc.identifier.issn1864-5917
dc.identifier.scopus2-s2.0-85170054014en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1007/s12065-023-00877-5
dc.identifier.urihttps://hdl.handle.net/20.500.14034/1268
dc.identifier.wosWOS:001062312700001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofEvolutionary Intelligenceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEngineering Design Optimization; Equilibrium Optimizer; Mutualism; Tangent Search Algorithmen_US
dc.titleDiversity enhanced Equilibrium Optimization algorithm for solving unconstrained and constrained optimization problemsen_US
dc.typeArticleen_US

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