摘要
讨论了一种解决柔性作业车间调度问题(FJSSP)的改进遗传算法,在FJSSP中考虑有一个具有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加工时间.FJSSP是作业车间调度问题(JSSP)的延伸,在FJSSP中每道工序的可选择加工的机器可能不止一台.FJSSP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.通过使用改进的遗传算法来搜索FJSSP的最优方案.并通过使用Brandimarte设计的10组不同规格的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,进一步证明了本改进遗传算法在解决FJSSP方面的有效性和实用性.
In this paper we discuss a improved genetic algorithm for flexible job shop scheduling problem （FJSSP）. In FJSSP we consid- er 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 own duration. FJSSP is the extension of job shop scheduling problem （ JSSP ） because there may have more than one machine to choose from for each working procedure. The goal is to find the shortest scheduling time in which none of the jobs＇ tasks collide on all of the m machines. This paper uses the improved Genetic Algorithm to find the optimal solution for FJSSP. Performance of the proposed beuristic is evaluated through computational experiments on 10 different sizes benchmarks designed by Brandimartc. The result of the test shows the efficiency of search is increased and the convergence is improved in FJSSP with the improved Genetic Algorithrn.
出处
《小型微型计算机系统》
CSCD
北大核心
2017年第1期129-132,共4页
Journal of Chinese Computer Systems
基金
国家科技重大专项(2013ZX04001-031)资助
关键词
柔性
调度
作业车间
改进
遗传算法
flexible
scheduling
job shop
improved
genetic algorithms
