A New Design of Metaheuristic Search Called Improved Monkey Algorithm Based on Random Perturbation for Optimization Problems

Basit Öğe Kaydı
dc.authoridhttps://orcid.org/0000-0001-8843-621Xen_US
dc.contributor.authorTunay, Mustafa
dc.date.accessioned2023-07-22T15:16:54Z
dc.date.available2023-07-22T15:16:54Z
dc.date.issued2021en_US
dc.departmentMühendislik ve Mimarlık Fakültesien_US
dc.description.abstractThe aim of this paper is to present a design of a metaheuristic search called improved monkey algorithm (MA+) that provides a suitable solution for the optimization problems. The proposed algorithm has been renewed by a new method using random perturbation (RP) into two control parameters (p1 and p2) to solve a wide variety of optimization problems. A novel RP is defined to improve the control parameters and is constructed off the proposed algorithm. The main advantage of the control parameters is that they more generally prevented the proposed algorithm from getting stuck in optimal solutions. Many optimization problems at the maximum allowable number of iterations can sometimes lead to an inferior local optimum. However, the search strategy in the proposed algorithm has proven to have a successful global optimal solution, convergence optimal solution, and much better performance on many optimization problems for the lowest number of iterations against the original monkey algorithm. All details in the improved monkey algorithm have been represented in this study. The performance of the proposed algorithm was first evaluated using 12 benchmark functions on different dimensions. These different dimensions can be classified into three different types: low-dimensional (30), medium-dimensional (60), and high-dimensional (90). In addition, the performance of the proposed algorithm was compared with the performance of several metaheuristic algorithms using these benchmark functions on many different types of dimensions. Experimental results show that the improved monkey algorithm is clearly superior to the original monkey algorithm, as well as to other well-known metaheuristic algorithms, in terms of obtaining the best optimal value and accelerating convergence solution.en_US
dc.identifier.doi10.1155/2021/5557259en_US
dc.identifier.endpage14en_US
dc.identifier.issn1058-9244
dc.identifier.issn1875-919X
dc.identifier.scopus2-s2.0-85106358163en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://hdl.handle.net/11363/5070
dc.identifier.urihttps://doi.org/
dc.identifier.volume2021en_US
dc.identifier.wosWOS:000664948600003en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorTunay, Mustafa
dc.language.isoenen_US
dc.publisherHINDAWI LTD, ADAM HOUSE, 3RD FLR, 1 FITZROY SQ, LONDON W1T 5HF, ENGLANDen_US
dc.relation.ispartofScientific Programmingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.titleA New Design of Metaheuristic Search Called Improved Monkey Algorithm Based on Random Perturbation for Optimization Problemsen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
5557259.pdf
Boyut:
1.45 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Makale / Article
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.56 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Web of Science ve Scopus Atıf Dizinlerindeki Yayınlar
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu