| 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. |
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| 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. |
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| A Genetic Algorithm Based Job-Shop Scheduling Problem Solving Method |
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CHEN En-hong,LIU Gui-quan,CAI Qing-sheng
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| 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. |
| Key words: Job-Shop scheduling, genetic algorithm. |
