摘要
偏柔性作业车间调度是生产管理中的重要问题。由于模型和计算的复杂性,传统优化方法往往难以得到最优解。采用改进遗传算法求解偏柔性作业车间的调度问题,设计相应的编码方法,利用所生成的染色体以及通过遗传操作得到的染色体生成可行的调度方案。基于工序串和机器串的编码方法,采用精英解保留策略、轮盘赌选择策略和基于划分集的交叉策略,提出基于均匀分布试验的变异法则,引入贪婪式解码方法对偏柔性作业车间调度进行求解。实例仿真表明,该算法在求解偏柔性作业车间调度方面具有良好的效率和优越性。
Partial flexible job-shop scheduling（PFJS） problem is considered and a genetic algorithm is presented for it.In the algorithm,job sequence and machine assignment are coded by job string and machine string,respectively.Thus,it is called a two-string encoding method.Based on the chromosome structure,it applies a selection strategy that uses elite reserving,roulette,and set-partition crossover operator.Meanwhile,for mutation,based on random experiment with uniform distribution,a strategy is proposed by selecting one among the reverse,circular interchange,inserting,and machine interchange operators.Further,greedy decoding procedure is adopted.A case study is presented to verify the effectiveness of the method.
出处
《工业工程》
北大核心
2010年第6期61-65,共5页
Industrial Engineering Journal
基金
国家自然科学基金资助项目(70671022)
关键词
偏柔性作业车间调度
遗传算法
交叉策略
变异操作
partial flexible job-shop scheduling
genetic algorithm
crossover strategy
mutation operation
