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 Li

Description

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.

Files

Institutions

Beijing University of Chemical Technology

Categories

Methodology

License