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题名: 柔性流水车间排产问题的一种协同进化CGA求解方法
其他题名: A co-evolution CGA solution for the flexible flow shop scheduling problem
作者: 韩忠华; 朱一行; 史海波; 林硕; 董晓婷
作者部门: 数字工厂研究室
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
刊名: 智能系统学报
ISSN号: 1673-4785
出版日期: 2015
卷号: 10, 期号:4, 页码:562-568
收录类别: CSCD
产权排序: 1
项目资助者: 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)
摘要: 为了解决柔性流水车间排产优化问题(flexible flow shop scheduling problem,FFSP),设计了一种动态协同进化紧致遗传算法(dynamic co-evolution compact genetic algorithm,DCCGA)作为全局优化算法。DCCGA算法基于FFSP特点,构建了描述问题解空间分布的概率模型,并对标准紧致遗传算法(compact genetic algorithm,CGA)的进化机制以及个体选择方式进行了改进。在其进化过程中,2个概率模型结合最优个体继承策略协同进化,并以一定的频率进行种群基因分布信息的交流,提高了算法进化过程中的种群基因...
英文摘要: 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 genetic algorithm ( CGA) for improving the evolutionary mechanism and individual selection method. DCCGA's 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 genetic 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 algorithm s. The results show that DCCGA is feasible for solving FFSP.
语种: 中文
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/17243
Appears in Collections:数字工厂研究室_期刊论文

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Recommended Citation:
韩忠华,朱一行,史海波,等. 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,2015,10(4):562-568.
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