Multi-population Modified L-SHADE for Single Objective Bound Constrained optimization

Yann Chern Jou, Shuo Ying Wang, Jia Fong Yeh, Tsung Che Chiang

研究成果: 書貢獻/報告類型會議論文篇章

摘要

In this paper, we extend a previous algorithm mL-SHADE by running the evolutionary process through multiple populations and adding dynamic control of mutation intensity and hyper-parameters. The whole population is partitioned into subpopulations by a random clustering method. Mutation intensity and hyper-parameters are adjusted based on the consumption of fitness function evaluations. Performance of the proposed algorithm is verified by ten benchmark functions in the CEC2020 Competition on Single Objective Bound Constrained optimization. The results show the competitiveness of the proposed algorithm.

原文英語
主出版物標題2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728169293
DOIs
出版狀態已發佈 - 2020 七月
事件2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Virtual, Glasgow, 英国
持續時間: 2020 七月 192020 七月 24

出版系列

名字2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings

會議

會議2020 IEEE Congress on Evolutionary Computation, CEC 2020
國家英国
城市Virtual, Glasgow
期間2020/07/192020/07/24

ASJC Scopus subject areas

  • Control and Optimization
  • Decision Sciences (miscellaneous)
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture

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