Parameter Setting of CMA-ES: A Numerical Study on CEC2019 100-Digit Challenge

Ting Yu Chen, Jia Fong Yeh, Tsung Su Yeh, Tsung Che Chiang

研究成果: 書貢獻/報告類型會議論文篇章

摘要

The evolution strategy with covariance matrix adaptation (CMA-ES) is a well-known algorithm in the family of evolution strategies. It consists of three main mechanisms: derandomized adaptation, cumulative step size, and covariance matrix adaptation. In this paper we aim to improve the CMA- ES and its performance by proper parameter values, better repair mechanism, removal of rank-one update, and a spread- based step size adaptation mechanism. We tested the proposed algorithm by ten test functions in the CEC2019 100-Digit Challenge. The results showed that our algorithm can achieve similar solution quality compared with two recent hybrid adaptive evolutionary algorithms and needs fewer fitness function evaluations.

原文英語
主出版物標題Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728146669
DOIs
出版狀態已發佈 - 2019 十一月
事件24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019 - Kaohsiung, 臺灣
持續時間: 2019 十一月 212019 十一月 23

出版系列

名字Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019

會議

會議24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
國家臺灣
城市Kaohsiung
期間2019/11/212019/11/23

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction

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