Novel Multi-Strategy Enhanced Whale Optimization Algorithm

Zong-Sing Huang, Wan-Ling Li
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Abstract

Whale Optimization Algorithm (WOA) is presented recently the state-of-the-art meta-heuristic optimization algorithm which has the critical advantages of fewer hyperparameters and simple framework. Unfortunately, WOA is not suitable to solve multimodal problems because of slow convergence. This paper proposes a novel multi-strategy enhanced whale optimization algorithm (MSEWOA) in order to improve WOA deal with multimodal ability. This paper has been completed testing with 23 benchmark functions. In experiments on multimodal problems with MSEWOA, it performed more effective than WOA and other conventional methods.
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一种新的多策略增强鲸鱼优化算法
鲸鱼优化算法(Whale Optimization Algorithm, WOA)是近年来提出的最先进的元启发式优化算法,具有超参数少、框架简单等关键优点。遗憾的是,由于收敛速度慢,WOA不适合解决多模态问题。为了提高WOA处理多模态的能力,提出了一种新的多策略增强型鲸鱼优化算法(MSEWOA)。本文已经完成了23个基准函数的测试。在多模态问题的实验中,MSEWOA比WOA和其他传统方法更有效。
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