Combined evolutionary algorithm for real parameters optimization

Jinn-Moon Yang*, C. Y. Kao

*Corresponding author for this work

研究成果: Paper

20 引文 斯高帕斯(Scopus)

摘要

The real coded genetic algorithms (RCGA) have proved to be more efficient than traditional bit-string genetic algorithm in parameter optimization, but the RCGA focuses on crossover operators and loss on the mutation operator for local search. Evolution strategies (ESs) and evolutionary programming (EP) only concern the Gaussian mutation operators. This paper proposes a technique, called combined evolutionary algorithm (CEA), by incorporating the ideas of EP and GAs into ES. Simultaneously, we add the local competition into the CEA in order to reduce the complexity and maintain the diversity. Over 20 benchmark function optimization problems are taken as benchmark problems. The results indicate that the CEA approach is a very powerful optimization technique.

原文English
頁面732-737
頁數6
DOIs
出版狀態Published - 1 一月 1996
事件Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96 - Nagoya, Jpn
持續時間: 20 五月 199622 五月 1996

Conference

ConferenceProceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96
城市Nagoya, Jpn
期間20/05/9622/05/96

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  • 引用此

    Yang, J-M., & Kao, C. Y. (1996). Combined evolutionary algorithm for real parameters optimization. 732-737. 論文發表於 Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96, Nagoya, Jpn, . https://doi.org/10.1109/ICEC.1996.542693