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基于遗传算法的Job-Shop调度问题求解方法
引用本文:陈恩红,刘贵全,蔡庆生. 基于遗传算法的Job-Shop调度问题求解方法[J]. 软件学报, 1998, 9(2): 139-143
作者姓名:陈恩红  刘贵全  蔡庆生
作者单位:中国科学技术大学计算机系,合肥,230027;中国科学技术大学计算机系,合肥,230027;中国科学技术大学计算机系,合肥,230027
基金项目:本文研究得到国家自然科学基金、国家教委博士点基金和中国科学技术大学青年基金资助.
摘    要:调度问题是许多计算机应用领域的重要问题,Job-Shop调度是其中的一类典型的困难问题,它通常包含多个可并行实现的目标以及实现这些目标的多种方法与资源.本文以一类实用的Job-Shop问题模型为基础,给出了用遗传算法求解调度问题应采用的染色体表示方法,并针对问题的特点,给出了面向资源空间与面向规划空间的遗传操作的设计思想与方法.实验结果表明,基于遗传算法的Job-Shop调度问题求解方法具有较好的性能,同时也表明,对于求解过程中可能出现的提前收敛问题可通过改变遗传操作概率及调节适应度等方法予以解决.

关 键 词:Job-Shop调度  遗传算法.
收稿时间:1997-01-20
修稿时间:1997-04-03

A Genetic Algorithm Based Job-Shop Scheduling Problem Solving Method
CHEN En-hong,LIU Gui-quan and CAI Qing-sheng. A Genetic Algorithm Based Job-Shop Scheduling Problem Solving Method[J]. Journal of Software, 1998, 9(2): 139-143
Authors:CHEN En-hong  LIU Gui-quan  CAI Qing-sheng
Affiliation:Department of Computer Science University of Science and Technology of China Hefei 230027
Abstract:Scheduling is an important problem for many computer application areas. Job-Shop scheduling is a typical kind of difficult problems among them. It usually comprises several parallel goals, methods and resources available to realize the goals. Based on a practical Job-Shop problem model, the paper presents a chromosome representation method for genetic algorithm based on the scheduling problem. To fully use the knowledge of the problem, the authors also propose resource-space oriented and plan-space oriented genetic operators. The experiment result demonstrates that the performance of the method is satisfactory, and it also shows that the pre-mature problem can be solved by dynamically changing the probability of genetic operators or by scaling the fitness values of chromosomes.
Keywords:Job-Shop scheduling   genetic algorithm.
本文献已被 CNKI 维普 万方数据 等数据库收录!
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