摘要
文章讨论了一个多目标车间调度问题(JSP)。在JSP问题中我们考虑一个具有n个工件和m台机器的生产线,每道工序在不同的机器上完成且有各自的持续时间。JSP调度问题的目标是在所有工件的工序在m台机器上加工且不冲突的前提下找到一个最短的总调度时间。该文通过使用遗传算法来找到作业调度问题的最优方案。文中通过使用11种不同规格的标准测试用例来测试算法的性能。实验结果表明,实验的运行结果满足了调度要求,进一步证明了遗传算法的有效性和实用性。
In this paper we consider a multiobjective job shop scheduling problem（ JSP）. In JSP we consider m machines on a production line with n defined jobs,each job consists of different tasks for different machines and each of them has its ow n duration. The goal is to find the shortest scheduling in which none of the jobs＇ tasks collide on all of the m machines. This part uses the Genetic Algorithm to find the optimal solution for the job scheduling problem. Performance of the proposed heuristic is evaluated through computational experiments on 11 different sizes benchmarks. The result of the test show s the efficiency of search is increased and the convergence is improved in shop scheduling with the Genetic Algorithm.
出处
《组合机床与自动化加工技术》
北大核心
2016年第5期43-45,50,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
"高档数控机床与基础制造装备"国家科技重大专项:基于二次开发平台的专用数控系统开发与应用(2013ZX04007-011)
关键词
作业调度
加工车间
遗传算法
启发式
多目标
scheduling
job shop
genetic algorithms
heuristic
multiobjective
