标题:A parameter adaptive DE algorithm on real-parameter optimization
作者:Pan, Jeng-Shyang; Yang, Cheng; Meng, Fanjia; Chen, Yuxin; Meng, Zhenyu
通讯作者:Meng, Zhenyu
作者机构:[Pan, Jeng-Shyang] Shandong Univ Sci & Technol, Coll Comp Sci & Engn, Qingdao, Peoples R China.; [Yang, Cheng; Chen, Yuxin; Meng, Zhenyu] Fujian Uni 更多
来源:JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
出版年:2020
卷:38
期:5
页码:5775-5786
DOI:10.3233/JIFS-179665
关键词:Adaptive update mechanism; differential evolution; real parameter; optimization; stochastic optimization
摘要:Differential Evolution (DE) algorithm generates a population of individuals by encoding with a floating point vector, and it is a simple and effective population-based stochastic optimization algorithm for global optimization of continuous space. Because of its excellent performance, DE variants can be applied in a wide range of applications in science and engineering. However, the performance of DE is sensitive to the choice of trial vector generation strategy and the associated control parameters. Therefore, it is necessary to choose appropriate mutation strategy and control parameters when tackling optimization applications. In this paper, an adaptive update mechanism is proposed to update control parameters F and Cr. The experimental results are verified on the CEC 2013 test suite which contains 28 benchmark functions for the evaluation of single objective real parameter optimization. The proposed algorithm is compared with jDE, iwPSO and ccPSO, and experiment results show its good performance.
收录类别:EI;SCOPUS;SCIE
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086699492&doi=10.3233%2fJIFS-179665&partnerID=40&md5=cdeba404fb4d6d85b4de8a8c51b93f6d
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