Fuzzy Adaptive Charged System Search for global optimization

Siamak Talatahari, Mahdi Azizi, Mehdi Toloo*

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةArticleمراجعة النظراء

11 اقتباسات (Scopus)


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.

اللغة الأصليةEnglish
رقم المقال107518
دوريةApplied Soft Computing
مستوى الصوت109
المعرِّفات الرقمية للأشياء
حالة النشرPublished - سبتمبر 2021

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