Comparison results of PR, SR and CS between MMSSA and state-of-the-art multimodal methods on 20 functions at different accuracy levels
Published: 12 January 2020| Version 1 | DOI: 10.17632/c37p323wvs.1
Contributor:
Hui LiDescription
We propose a multimodal version of squirrel search algorithm named as MMSSA. When solving multimodal optimization problems, MMSSA combines squirrel search with clustering, crowding, and sampling techniques to enhance its multimodal optimization ability. We tested MMSSA on twenty functions recommended by CEC'2013 which was specifically designed as benchmark problems for multimodal optimization.
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Institutions
Beijing University of Chemical Technology
Categories
Methodology