Chameleon Swarm Algorithm: A bio-inspired optimizer for solving engineering design problems
作者：
Highlights：
• Chameleon Swarm Algorithm (CSA) is benchmarked on 67 benchmark functions.
• The exploitation ability of CSA is affirmed by the results on unimodal functions.
• The results of CSA on multimodal functions show the exploration ability of CSA.
• The results of CSA on composite functions prove the reliability level of CSA.
• The results on five engineering problems affirm the accuracy of CSA in practice.
摘要
•Chameleon Swarm Algorithm (CSA) is benchmarked on 67 benchmark functions.•The exploitation ability of CSA is affirmed by the results on unimodal functions.•The results of CSA on multimodal functions show the exploration ability of CSA.•The results of CSA on composite functions prove the reliability level of CSA.•The results on five engineering problems affirm the accuracy of CSA in practice.
论文关键词：Chameleon Swarm Algorithm,Optimization techniques,Meta-heuristics,Nature-inspired algorithms,Evolutionary algorithms,Swarm intelligence algorithms
论文评审过程：Received 18 April 2020, Revised 3 February 2021, Accepted 4 February 2021, Available online 12 February 2021, Version of Record 8 March 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.114685
