A new accurate and fast convergence cuckoo search algorithm for solving constrained engineering optimization problems

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dc.authorscopusidBahman Arasteh / 39861139000
dc.authorwosidBahman Arasteh / AAN-9555-2021
dc.contributor.authorAbdollahi, Mahdi
dc.contributor.authorBouyer, Asgarali
dc.contributor.authorArasteh, Bahman
dc.date.accessioned2025-04-16T20:18:04Z
dc.date.available2025-04-16T20:18:04Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümü
dc.description.abstractIn recent years, the Cuckoo Optimization Algorithm (COA) has been widely used to solve various optimization problems due to its simplicity, efficacy, and capability to avoid getting trapped in local optima. However, COA has some limitations such as low convergence when it comes to solving constrained optimization problems with many constraints. This study proposes a new modified and adapted version of the Cuckoo optimization algorithm, referred to as MCOA, that overcomes the challenge of solving constrained optimization problems. The proposed adapted version introduces a new coefficient that reduces the egg-laying radius, thereby enabling faster convergence to the optimal solution. Unlike previous methods, the new coefficient does not require any adjustment during the iterative process, as the radius automatically decreases along the iterations. To handle constraints, we employ the Penalty Method, which allows us to incorporate constraints into the optimization problem without altering its formulation. To evaluate the performance of the proposed MCOA, we conduct experiments on five well-known case studies. Experimental results demonstrate that MCOA outperforms COA and other state-of-the-art optimization algorithms in terms of both efficiency and robustness. Furthermore, MCOA can reliably find the global optimal solution for all the tested problems within a reasonable iteration number. © 2024 – IOS Press. All rights reserved.
dc.identifier.citationAbdollahi, M., Bouyer, A., & Arasteh, B. (2024). A new accurate and fast convergence cuckoo search algorithm for solving constrained engineering optimization problems. Intelligent Decision Technologies, 18(3), 2307-2337.
dc.identifier.doi10.3233/IDT-240306
dc.identifier.endpage2337
dc.identifier.issn18724981
dc.identifier.issue3
dc.identifier.scopusqualityQ3
dc.identifier.startpage2307
dc.identifier.urihttp://dx.doi.org/10.3233/IDT-240306
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6074
dc.identifier.volume18
dc.identifier.wosWOS:001325852500010
dc.identifier.wosqualityQ4
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorArasteh, Bahman
dc.institutionauthoridBahman Arasteh / 0000-0001-5202-6315
dc.language.isoen
dc.publisherIOS Press BV
dc.relation.ispartofIntelligent Decision Technologies
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectConstrained Problems
dc.subjectCuckoo Optimization Algorithm
dc.subjectEngineering Designing Problems
dc.subjectNonlinear Optimization Problem
dc.subjectPenalty Function
dc.titleA new accurate and fast convergence cuckoo search algorithm for solving constrained engineering optimization problems
dc.typeArticle

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