Polychromatic-sets-based improved genetic algorithm for solving multi-species FJSP

被引：0

作者：

Fu, Wei-Ping ^{[1
]}

Liu, Dong-Mei ^{[1
,2
]}

Lai, Chun-Wei ^{[1
]}

Wang, Wen ^{[1
]}

机构：

[1] School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China

[2] Department of Management, Xijing University, Xi'an 710123, China

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2011年 / 17卷 / 05期

关键词：

Job shop scheduling - Signal encoding - Encoding (symbols);

D O I：

暂无

中图分类号：

学科分类号：

摘要：

To avoid premature or convergence of conventional genetic algorithm, an improved genetic algorithm based on polychromatic sets theory was presented. In the process of encoding, decoding and mutation, by searching the contour matrix, the algorithm speed was improved therefore the solution efficiency was improved. Then, single encoding was used to represent the double-constrained scheduling problems to reduce time and space complexity of the improved genetic algorithm. Comparison of examples verified that the improved genetic algorithm was feasible and effective, which could be used to deal with Flexible Job-Shop Scheduling Problem (FJSP).

引用

页码：1004 / 1010

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