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基于佳点集遗传算法求解Job-shop调度问题 被引量：3

Solving Job-Shop Scheduling Problem Using Good Point Set Based Genetic Algorithm
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摘要 1.介绍 Job-shop调度同题(JSSP)是极为困难的带约束组合优化问题,是NP难的.典型的Job-shop调度问题可描述为n个工件要在m台机器上加工,每个工件有其特定的加工工序,每道工序加工时间已知,并符合以下假设[1]: Job-shop is the representative of constrained combinatorial optimization problem and extremely hard to solve. By analyzing the crossover operation, that is choosing a point in the family whose ancestors have schema of high fitness, we utilize the principles of good point set in number theory and redesign the crossover operator. Then a new GA called good point set based GA is presented and applied to solve the benchmark problem of MT06 and MT10. The experimental result shows this new GA works well.
作者 程军盛 张铃
机构地区 安徽大学人工智能研究所
出处 《计算机科学》 CSCD 北大核心 2002年第4期67-68,共2页 Computer Science
基金 973基金(G98030509)
关键词 JOB-SHOP调度问题 组合优化问题 佳点集遗传算法 启发式算法 Good point set based Genetic algorithm, Job-shop scheduling problem, Combinatorial optimization
分类号 O224 [理学—运筹学与控制论] O242.23 [理学—计算数学]
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参考文献7

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二级参考文献9

共引文献164

同被引文献24

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计算机科学
2002年 第4期

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