Hybrid ant colony algorithm for fuzzy Job Shop scheduling

被引：0
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作者：
Shenyang Inst. of Automation, Chinese Academy of Sciences, Shenyang 110016, China [1 ]
不详 [2 ]
机构：
来源：
Jisuanji Jicheng Zhizao Xitong | 2007年 / 1卷 / 105-109+125期
关键词：
Combinatorial optimization - Fuzzy control - Genetic algorithms - Heuristic algorithms - Machine shops - Mathematical models - Scheduling - Tabu search;
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摘要：
Due to the low efficiency of ant colony algorithms and easily plunged into local optimal, a hybrid ant colony algorithm for fuzzy Job Shop scheduling was proposed. In this method, the ant colony algorithm was served as a global search algorithm. According to the characteristics of Job Shop scheduling, a new TS algorithm based on the critical operation was presented, which was used as the local search algorithm in the hybrid ant colony algorithm. Because of the stronger local search ability of TS algorithm, this hybrid algorithm could improve the solutions quality. Experimental results verified the effectiveness of the proposed hybrid algorithm by comparing with TS algorithm and parallel genetic algorithms.
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