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A dynamic co-evolution compact genetic algorithm for E/T problem
Han ZH(韩忠华); Zhu YX(朱一行); Lin S(林硕)
作者部门数字工厂研究室
会议名称17th IFAC Symposium on System Identification, SYSID 2015
会议日期October 19-21, 2015
会议地点Beijing, China
会议录名称17th IFAC Symposium on System Identification, SYSID 2015
出版者IFAC
出版地Laxenburg, AUSTRIA
2015
页码1439-1443
收录类别EI
EI收录号20163902851565
产权排序1
关键词Probabilistic Models Dynamic Co-evolution Compact Genetic Algorithm Flexible Flow Shop Earliness Tardiness (E/t)
摘要In 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.
语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/19248
专题数字工厂研究室
作者单位1.Faculty of Information and Control Engineering, Shenyang Jianzhu University, Department of Digital Factory, Shenyang Institute of Automation, Key Laboratory of networked control system, Shenyang, China
2.Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, China
推荐引用方式
GB/T 7714
Han ZH,Zhu YX,Lin S. A dynamic co-evolution compact genetic algorithm for E/T problem[C]. Laxenburg, AUSTRIA:IFAC,2015:1439-1443.
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