首页> 外文期刊>Control Systems Technology, IEEE Transactions on >A Scatter Search Algorithm for a Multistage Production Scheduling Problem With Blocking and Semi-Continuous Batching Machine
【24h】

A Scatter Search Algorithm for a Multistage Production Scheduling Problem With Blocking and Semi-Continuous Batching Machine

机译:带有分块和半连续配料机的多阶段生产计划问题的散点搜索算法

获取原文
获取原文并翻译 | 示例
       

摘要

This paper studies a multistage production scheduling problem with blocking and semi-continuous batching machine, which is abstracted from the integrated hot rolling production in iron and steel industry. One major characteristic of the problem is that the first machine is a semi-continuous batching machine that can simultaneously process multiple jobs and the jobs do not enter and leave it in a batch mode, but one by one and continuously. Furthermore, this problem considers multiple production stages of hot rolling line while previous problems in the literature focused on only the single hot rolling stage or the two stages of reheating and hot rolling. This problem can be treated as a generalized permutation flowshop scheduling problem with blocking to minimize the makespan (i.e., the maximum completion time of all jobs), which is a NP-hard problem. We formulate this problem as a mixed integer linear programming model and propose a scatter search (SS) algorithm to solve it. To further improve the performance of the SS, the reference set is divided into three parts to balance the solution quality and diversity, and a modified stochastic variable neighborhood search is developed as the local search, where two kinds of speedup strategies based on the problem's characteristics are incorporated. Computational results on practical production data and randomly generated instances of our problem show that the SS algorithm outperforms the commercial software named CPLEX and some other meta-heuristics. In addition, further tests using benchmark instances of the traditional permutation flowshop scheduling problem with blocking also demonstrate that our SS algorithm is superior to previous meta-heuristics in the literature.
机译:本文从钢铁行业的综合热轧生产中抽象出了分块半连续配料机的多阶段生产调度问题。该问题的一个主要特征是,第一台机器是半连续配料机,它可以同时处理多个作业,并且这些作业不会以批处理模式进入和离开它,而是一个接一个地连续进行。此外,该问题考虑了热轧生产线的多个生产阶段,而文献中先前的问题仅集中在单个热轧阶段或再加热和热轧两个阶段。这个问题可以看作是一般的排列流水车间调度问题,它具有阻塞以最小化制造期(即所有作业的最大完成时间),这是一个NP难题。我们将此问题公式化为混合整数线性规划模型,并提出了一种分散搜索(SS)算法来解决该问题。为了进一步提高SS的性能,将参考集分为三个部分以平衡解决方案的质量和多样性,并开发了一种改进的随机变量邻域搜索作为局部搜索,其中基于问题的特征提供了两种加速策略被合并。在实际生产数据和我们问题的随机生成实例上的计算结果表明,SS算法优于名为CPLEX的商业软件和其他一些元启发式算法。此外,使用带有置换的传统置换Flowshop调度问题的基准实例进行的进一步测试还表明,我们的SS算法优于文献中先前的元启发式算法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号