Hybrid beluga whale optimization algorithm with multi-strategy for functions and engineering optimization problems

Hybrid beluga whale optimization algorithm with multi-strategy for functions and engineering optimization problems

Abstract Beluga Whale Optimization (BWO) is a new metaheuristic algorithm that simulates the social behaviors of beluga whales swimming, foraging, and whale falling. Compared with other optimization algorithms, BWO shows certain advantages in solving unimodal and multimodal optimization problems. Ho...

書誌詳細
主要な著者:	Jiaxu Huang, Haiqing Hu
フォーマット:	論文
言語:	English
出版事項:	SpringerOpen 2024-01-01
シリーズ:	Journal of Big Data
主題:	Beluga whale optimization Quasi-oppositional based learning The adaptive and spiral predation strategies Nelder-Mead simplex search Engineering design
オンライン･アクセス:	https://doi.org/10.1186/s40537-023-00864-8

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