Applying family competition to evolution strategies for constrained optimization

Jinn Moon Yang, Ying Ping Chen, Jorng Tzong Horng, Cheng Yan Kao

研究成果: 書貢獻/報告類型會議論文篇章同行評審

81 引文 斯高帕斯(Scopus)


This paper applies family competition to evolution strategies to solve constrained optimization problems. The family competition of Family Competition Evolution Strategy (FCES) can be viewed as a local competition involving the children generated from the same parent, while the selection is a global competition among all of the members in the population. According to our experimental results, the self-adaptation of strategy parameters with deterministic elitist selection may trap ESs into local optima when they are applied to heavy constrained optimization problems. By controlling strategy parameters with non-self adaptive rule, FCES can reduce the computation time of self-adaptive Gaussian mutation, diminish the complexity of selection from (m+l) to (m+m), and avoid to be premature. Therefore, FCES is capable of obtaining better performance and saving the computation time. In this paper, FCES is compared with other evolutionary algorithms on various benchmark problems and the results indicate that FCES is a powerful optimization technique.

主出版物標題Evolutionary Programming VI - 6th International Conference, EP 1997, Proceedings
編輯Peter J. Angeline, Robert G. Reynolds, John R. McDonnell, Russ Eberhart
發行者Springer Verlag
出版狀態已出版 - 1997
事件6th International Conference on Evolutionary Programming, EP 1997 - Indianapolis, United States
持續時間: 13 4月 199716 4月 1997


名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)


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國家/地區United States


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