智能系统学报Issue(4)：562-568,7.DOI:10.3969/j.issn.1673-4785.201503045
柔性流水车间排产问题的一种协同进化 CGA 求解方法
A co-evolution CGA solution for the flexible flow shop scheduling problem
摘要
Abstract
In order to solve the flexible flow shop scheduling problem (FFSP), a dynamic co-evolution compact genetic algorithm (DCCGA) is designed as the global optimization algorithm.In DCCGA, a probabilistic model is constructed to describe the distribution of solutions of the problem, and two modifications are incorporated in the standard compact ge-netic algorithm ( CGA) for improving the evolutionary mechanism and individual selection method.DCCGAˊs evolutionary process is led by two probabilistic models, which contains the optimal individual inheritance strategy, and communicates with each other at a certain frequency with the population genetic information .Hence, the diversity of the population ge-netic information is improved during the process, and also the stability of good evolutionary trend and the capacity of continuous evolution are greatly strengthened at the same time.Moreover, the suitable parameter value is suggested based on relative experiments.And, DCCGA is measured by the benchmark problems with comparison of several effective algo-rithm s.The results show that DCCGA is feasible for solving FFSP.关键词
双概率模型/动态协同进化/最优个体继承策略/紧致遗传算法/柔性流水车间Key words
bi-probabilistic models/dynamic co-evolution/optimal individual inheritance strategy/compact genetic algorithm/flexible flow shop分类
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韩忠华,朱一行,史海波,林硕,董晓婷..柔性流水车间排产问题的一种协同进化 CGA 求解方法[J].智能系统学报,2015,(4):562-568,7.基金项目
中科院重点实验室开放课题资助；国家重大科技专项资助项目（2011ZX02601－005）． （）
