Self-adaptive Equilibrium Optimizer for solving global, combinatorial, engineering, and Multi-Objective problems

Basit Öğe Kaydı
dc.authoridHoussein, Essam Halim/0000-0002-8127-7233
dc.authorwosidHoussein, Essam Halim/C-8941-2016
dc.contributor.authorHoussein, Essam H.
dc.contributor.authorÇelik, Emre
dc.contributor.authorMahdy, Mohamed A.
dc.contributor.authorGhoniem, Rania M.
dc.date.accessioned2023-07-26T11:54:21Z
dc.date.available2023-07-26T11:54:21Z
dc.date.issued2022
dc.departmentDÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractThis paper proposes a self-adaptive Equilibrium Optimizer (self-EO) to perform better global, combinatorial, engineering, and multi-objective optimization problems. The new self-EO algorithm integrates four effective exploring phases, which address the potential shortcomings of the original EO. We validate the performances of the proposed algorithm over a large spectrum of optimization problems, i.e., ten functions of the CEC'20 benchmark, three engineering optimization problems, two combinatorial optimization problems, and three multi-objective problems. We compare the self-EO results to those obtained with nine other metaheuristic algorithms (MAs), including the original EO. We employ different metrics to analyze the results thoroughly. The self-EO analyses suggest that the self-EO algorithm has a greater ability to locate the optimal region, a better trade-off between exploring and exploiting mechanisms, and a faster convergence rate to (near)-optimal solutions than other algorithms. Indeed, the self-EO algorithm reaches better results than the other algorithms for most of the tested functions.en_US
dc.identifier.doi10.1016/j.eswa.2022.116552
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.scopus2-s2.0-85124155587en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2022.116552
dc.identifier.urihttps://hdl.handle.net/20.500.12684/12809
dc.identifier.volume195en_US
dc.identifier.wosWOS:000761969600005en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorÇelik, Emre
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz$2023V1Guncelleme$en_US
dc.subjectEquilibrium Optimizer; Enhanced Equilibrium Optimizer (Self-Eo); Multi-Objective Self-Eo (Mo-Self-Eo); Engineering Design Problems; Combinatorial Optimization Problems; Metaheuristic Algorithms (Mas)en_US
dc.subjectColony Optimization; Algorithm; Searchen_US
dc.titleSelf-adaptive Equilibrium Optimizer for solving global, combinatorial, engineering, and Multi-Objective problemsen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
12809.pdf
Boyut:
3.13 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu