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求解作业车间调度问题的一种改进遗传算法
引用本文:张超勇,饶运清,李培根,刘向军.求解作业车间调度问题的一种改进遗传算法[J].计算机集成制造系统,2004,10(8):966-970.
作者姓名:张超勇  饶运清  李培根  刘向军
作者单位:华中科技大学,机械科学与工程学院,湖北,武汉,430074
基金项目:国家自然科学基金资助项目(50105006,50305008)。~~
摘    要:为克服传统遗传算法解决车间作业调度问题的局限性,综合遗传算法和局部搜索的优点,提出一种改进的遗传算法。为基于工序的编码提出了一种新的POX交叉算子。同时,为克服传统遗传算法在求解车间作业调度问题时的早熟收敛,设计了一种子代交替模式的交叉方式,并运用局部搜索改善交叉和变异后得到的调度解,将提出的改进遗传算法应用于MuthandThompson基准问题的实验运行,显示了该算法的有效性。

关 键 词:车间作业调度  遗传算法  交叉算子  局部搜索
文章编号:1006-5911(2004)08-0966-05
修稿时间:2003年7月15日

An improved genetic algorithm for Job-Shop scheduling
ZHANG Chao-yong,RAO Yun-qing,LI Pei-gen,LIU Xiang-jun.An improved genetic algorithm for Job-Shop scheduling[J].Computer Integrated Manufacturing Systems,2004,10(8):966-970.
Authors:ZHANG Chao-yong  RAO Yun-qing  LI Pei-gen  LIU Xiang-jun
Abstract:To overcome the limitations of traditional Genetic Algorithm (GA) when solving the problem of job-shop scheduling, an improved GA was proposed by taking advantages of traditional GA and local search. A new crossover operator, Precedence Operation Crossover (POX), for operation-based representation was created. To avoid premature convergence, which appeared in the course of solving job-shop scheduling by applying conventional GA. The concept of an improved generation alteration model was introduced. After a schedule was obtained, a local search heuristic was applied to improve the solution. Its efficiency was validated by applying improved GA to Muth and Thompson's benchmark problem.
Keywords:job-shop scheduling  genetic algorithm  crossover operator  local search
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