Fuzzy Adaptive Charged System Search for global optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F21%3A10247574" target="_blank" >RIV/61989100:27510/21:10247574 - isvavai.cz</a>

Výsledek na webu

<a href="https://reader.elsevier.com/reader/sd/pii/S1568494621004415?token=F994DA31A698D353073F2BED73A269EC182901F3C78331D11BAC24DF6E254B6F8F7C76FA9EC2C135A04E352D016C6016&originRegion=eu-west-1&originCreation=20210709080054" target="_blank" >https://reader.elsevier.com/reader/sd/pii/S1568494621004415?token=F994DA31A698D353073F2BED73A269EC182901F3C78331D11BAC24DF6E254B6F8F7C76FA9EC2C135A04E352D016C6016&originRegion=eu-west-1&originCreation=20210709080054</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.asoc.2021.107518" target="_blank" >10.1016/j.asoc.2021.107518</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fuzzy Adaptive Charged System Search for global optimization

Popis výsledku v původním jazyce

This study proposes a new fuzzy adaptive Charged System Search (CSS) for global optimization. The suggested algorithm includes a parameter tuning process based on fuzzy logic with the aim of improving its performance. In this regard, four linguistic variables are defined which configures a fuzzy system for parameter identification of the standard CSS algorithm. This process provides a focus for the algorithm on higher levels of global searching in the initial iterations while the local search is considered in the last iterations. Twenty mathematical benchmark functions, the Competitions on Evolutionary Computation (CEC) regarding CEC 2020 benchmark, three well-known constrained, and two engineering problems are utilized to validate the new algorithm. Moreover, the performance of the new algorithm is compared and contrasted with other metaheuristic algorithms. The obtained results reveal the superiority of the proposed approach in dealing with different unconstraint, constrained, and engineering design problems. (C) 2021 Elsevier B.V.

Název v anglickém jazyce

Fuzzy Adaptive Charged System Search for global optimization

Popis výsledku anglicky

This study proposes a new fuzzy adaptive Charged System Search (CSS) for global optimization. The suggested algorithm includes a parameter tuning process based on fuzzy logic with the aim of improving its performance. In this regard, four linguistic variables are defined which configures a fuzzy system for parameter identification of the standard CSS algorithm. This process provides a focus for the algorithm on higher levels of global searching in the initial iterations while the local search is considered in the last iterations. Twenty mathematical benchmark functions, the Competitions on Evolutionary Computation (CEC) regarding CEC 2020 benchmark, three well-known constrained, and two engineering problems are utilized to validate the new algorithm. Moreover, the performance of the new algorithm is compared and contrasted with other metaheuristic algorithms. The obtained results reveal the superiority of the proposed approach in dealing with different unconstraint, constrained, and engineering design problems. (C) 2021 Elsevier B.V.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/GA19-13946S" target="_blank" >GA19-13946S: Hodnocení výkonnosti při výskytu neklasifikovaných faktorů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Applied Soft Computing

ISSN

1568-4946

e-ISSN

—

Svazek periodika

109

Číslo periodika v rámci svazku

september

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

18

Strana od-do

107518

Kód UT WoS článku

000685652800011

EID výsledku v databázi Scopus

2-s2.0-85107042524