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Journal of Computers EIMEDLINEScopus

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篇名 Integration Differential Evolution Algorithm with Dynamic Multiple Population Base on Weighted Strategies
卷期 30:5
作者 Yu-Ling Fan 、 Jia-Neng Tang 、 Pei-Zhong Liu 、 Yan-Ming Luo 、 Xiao-Fang Liu
頁次 046-059
關鍵字 differential evolution 、 multiple populations 、 parabola increment 、 weighted strategy 、 EI 、 MEDLINE 、 Scopus
出刊日期 201910
DOI 10.3966/199115992019103005004

中文摘要

英文摘要

Integration differential evolution algorithm with dynamic multiple population base on weighted strategies (MPWDE) is a kind of heuristic random search algorithm, which is used to solve global optimization problems. Firstly, the population is divided into several sub populations, which improves the diversity of the population at the initial stage of the population. Meanwhile, the population diversity is improved by the parabola increment crossover factor in evolutionary process. Then, by introducing weighted strategies mechanism, the mutation strategy “DE/current-to-pbest/2 or DE/current-to-rbest/2” improves the convergence speed of the algorithm. Finally, the numerical simulation results show the effectiveness of the proposed algorithm, compared with the state-of-the-art algorithms on CEC2006 benchmark functions.

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