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A genetic algorithm applied to a classic job-shop scheduling problem
被引：7
作者：
Shi, G
机构：
[1] Kyoto Inst of Technology, Kyoto, Japan
关键词：
Computational complexity - Convergence of numerical methods - Machinery - Optimization - Scheduling;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Job-shop scheduling is essentially an ordering problem. A new encoding scheme for a classic job-shop scheduling problem is presented, by which a schedule directly corresponds to an ordering string. For the new encoding, a simple but highly effective crossover operation is contrived, and the problem of infeasibility in genetic generation is naturally overcome. Within the framework of the newly designed genetic algorithm, the NP-hard classic job-shop scheduling problem can be efficiently solved with high quality. Moreover the optimal solutions of the two famous benchmarks, the Fisher and Thompson's 10 x 10 and 20 x 5 problems, are found.
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页码：25 / 32
页数：8
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