文章基本信息

标题：A dynamic co-evolution compact genetic algorithm for E/T problem
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作者：Zhonghua Han ; Yihang Zhu ; Shuo Lin 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2015
卷号：48
期号：28
页码：1439-1443
DOI：10.1016/j.ifacol.2015.12.335
语种：English
出版社：Elsevier
摘要：AbstractIn this paper, a dynamic co-evolution compact genetic algorithm (DCCGA) is proposed for flexible flow shop scheduling problem (FFSP) to minimize the total earliness and tardiness (E/T) penalties. In this new algorithm, a dynamic co-evolution mechanism containing two probabilistic models and a best individual inheritance strategy are integrated into the compact genetic algorithm (CGA). For improving the stability of the evolutionary trend in the evolution processes, the diversity of evolution trend and the convergence speed. Lastly, the experimental results show that, DCCGA outperforms CGA by 11.74% on the problem we study.
关键词：Keywordsprobabilistic modelsdynamic co-evolutioncompact genetic algorithmflexible flow shopearliness tardiness (E/T)