Chameleon Swarm Algorithm for Segmental Variation Learning of Population and S-type Weight

Authors

Damin Zhang, 1.School of Big Data & Information Engineering, Guizhou University, Guiyang 550025, China;Follow
Yi Wang, 1.School of Big Data & Information Engineering, Guizhou University, Guiyang 550025, China;Follow
Linna Zhang, 2.School of Mechanical Engineering, Guizhou University, Guiyang 550025, China;

Abstract

Abstract: It is the best choice for intelligent algorithms to be applied to specific fields to explore strong searching ability, good reliability and stability.In this paper, aiming at the defects of chameleon swarm algorithm, such as unstable solution, low convergence accuracy and unbalanced search and development, a chameleon swarm algorithm (RMSCSA) based on population diversity segmental mutation learning and S-type weight is proposed. The refraction mirror learning strategy (RML) is introduced to make the chameleon more consistent with the observation in nature and enhance its diversity. The introduction of segmental variation of population diversity can keep the individuals with poor fitness and guide them to the optimal position. The introduction of S-type decreasing weight makes it further balance the global search and explore ability of the algorithm, and obtains the advantage of S-type decreasing weight factor through convergence analysis. The classical test function and CEC 2017 competition function are used for performance verification, and the results show that the three strategies have better optimization accuracy and efficiency for CSA. In order to compare the performance of different algorithms, the results of 30 independent runs are statistically analyzed by Wilcoxon rank-sum test, Friedman's test and Holm follow-up test. The analysis shows that the three strategies introduced have better optimization ability compared with CSA.

Recommended Citation

Zhang, Damin; Wang, Yi; and Zhang, Linna (2023) "Chameleon Swarm Algorithm for Segmental Variation Learning of Population and S-type Weight," Journal of System Simulation: Vol. 35: Iss. 1, Article 2.
DOI: 10.16182/j.issn1004731x.joss.21-0968
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss1/2

First Page

11

Revised Date

2021-11-10

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-0968

Last Page

26

CLC

TP301.6

Recommended Citation

Damin Zhang, Yi Wang, Linna Zhang. Chameleon Swarm Algorithm for Segmental Variation Learning of Population and S-type Weight[J]. Journal of System Simulation, 2023, 35(1): 11-26.

Corresponding Author

Yi Wang,ywang_gzu@163.com

DOI

10.16182/j.issn1004731x.joss.21-0968