引用本文:袁帅鹏,李铁克,王柏琳.带运输时间混合流水车间成组调度的协同进化文化基因算法[J].控制理论与应用,2023,40(3):430~440.[点击复制]
Yuan Shuai-peng,Li Tie-ke,Wang Bai-lin.Co-evolutionary memetic algorithm for the hybrid flow shop group scheduling with transportation times[J].Control Theory and Technology,2023,40(3):430~440.[点击复制]
带运输时间混合流水车间成组调度的协同进化文化基因算法
Co-evolutionary memetic algorithm for the hybrid flow shop group scheduling with transportation times
摘要点击 1565  全文点击 581  投稿时间:2021-08-24  修订日期:2023-02-23
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DOI编号  10.7641/CTA.2022.10779
  2023,40(3):430-440
中文关键词  混合流水车间  成组调度  运输时间  协同进化  文化基因算法
英文关键词  hybrid flowshop  group scheduling  transportation time  co-evolutionary  memetic algorithm
基金项目  国家自然科学基金项目(71701016, 71231001), 北京市自然科学基金项目(9174038), 中央高校基本科研业务费项目(FRF??BD??20??16A)资助.
作者单位E-mail
袁帅鹏* 北京科技大学 17801002601@163.com 
李铁克 北京科技大学  
王柏琳 北京科技大学  
中文摘要
      研究了一类带有序列相关准备时间和阶段间运输时间的混合流水车间成组调度问题, 以最小化最大完 工时间为目标建立混合整数线性规划模型, 结合问题特征提出一种协同进化文化基因算法. 算法采用置换序列 的方式对工件组间调度、各工件组内工件间调度以及各工件组在各阶段上并行机的指派3个子问题进行统一编 码, 基于负载均衡思想和改进的先到先得策略将染色体解码为问题的可行解; 进化过程中采用多种遗传算子执 行全域搜索, 并设计了一种基于破坏和重新构造的协同进化局部搜索策略. 通过不同问题规模的数据实验和与 对比算法的比较分析, 验证了所提模型和算法的有效性.
英文摘要
      This study investigates the hybrid flow shop group scheduling problem with sequence-dependent setup time between groups and job transportation time between machines. A mixed integer linear programming model for minimizing the makespan is established at first. A co-evolutionary memetic algorithm (CMA) is then proposed in view of the problem’s feature. In the CMA, the three sub-problems, namely group scheduling, job scheduling within each group and its assignment at each stage, are coded uniformly, and the chromosome is decoded into a feasible solution based on the idea of load balancing and an improved first-come-first-served strategy. A variety of genetic operators are used to perform a global search during the evolution process, and a collaborative optimization local search strategy based on destruction and reconstruction is designed. Experiments with various problem scales are carried out, and the results verify the efficiency and robustness of the proposed algorithm.