摘要
古典作业车间调度问题已经被研究了几十年并证明为 NP- hard问题。柔性作业车间调度是古典作业车间调度问题的扩展 ,它允许工序可以由一个机床集合中的多台机床完成加工 ,调度的目的是将工序分配给各机床 ,并对各机床上的工序进行排序以使完成所有工序的时间最小化。本文采用遗传算法进行柔性作业车间调度研究 ,针对柔性作业车间问题提出了一种新颖直观的基因编码方法以适用于批量调度 ,并分析了几种批量调度方案 ,最后给出了这些调度的仿真结果 。
The job shop scheduling problem has been studied for decades and known as NP hard problem. The flexible job shop scheduling problem is an extension of the classical job scheduling problem that allows one operation to be processed on several machines out of a set of machines. The problem is to assign each operation to a machine and find a sequence for the operations on the machine in order that the completion time of all operations is minimized. A new encoding scheme for batch process schedule is presented. Several batch process scheduling schemes are analyzed. Finally, the results of these schemes are shown and it is confirmed that the optimum schedule of general scheduling is not fitted for batch process scheduling.
出处
《机械科学与技术》
CSCD
北大核心
2002年第3期348-350,354,共4页
Mechanical Science and Technology for Aerospace Engineering
基金
国家自然科学基金重大项目 (5 9990 470 )资助
关键词
柔性作业车间
批量调度
遗传算法
Flexible job shop
Batch process schedule
Genetic algorithms
