全文下载：2012050489
王硕，顾幸生*
（华东理工大学 化工过程先进控制和优化技术教育部重点实验室,上海 200237）
摘要： 提出了一种改进的蚁群算法，应用于经典的作业车间调度问题。编码采用基于机器的编码可以控制冗余解的数量，但同时会产生不可行解。本研究提出了控制不可行解产生的策略,同时对已出现的不可行解问题，在尽量保留种群基因的前提下，改变解的形式加以利用。在丰富了种群的多样性的同时解决了不可行解的问题。采用自适应参数法则，使参数的变化顺应种群发展过程各个阶段的需要。在一定代数的迭代后，通过改变某些参数跳出局部最优，从而达到了较好的搜索效果。
关键词：作业车间调度； 蚁群算法； 不可行解； 自适应参数
中图分类号： TP 301文献标志码： A
Job Shop Scheduling Based on Improved Ant Colony Algorithm
WANG Shuo，GU Xing-sheng
（Key Laboratory of Advanced Control and Optimization for Chemical Processes,Ministry of Education, East China University of Science and Technology,Shanghai,200237）
Abstract: The improved ant colony algorithm is proposed and applied to solving the job shop scheduling problem. Using machine based coding，redundancy solution is perfectly limited. However, infeasible solutions can be generated by such coding method. In this paper, strategies to limit the infeasible solutions are put forward and the infeasible solution is transformed into feasible solution at the same time. Such strategies not only preserve the population in rich diversity, but also solved the problem of infeasible solutions. Adaptive parameter laws are issued to make the parameters changing every moment,which met the demands of population at all stages of evolution. After certain iterations, the algorithm may get out of local optimal value by merely changing some parameters. Finally, better searching results have been achieved.
Key words： job shop scheduling； ant colony algorithm； infeasible solution； adaptive parameter
收稿日期：2012-06-04
作者简介： 王硕（1987—），男，硕士研究生.*通信联系人
