东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2008, Vol. 29 ›› Issue (4): 561-564.DOI: -

• 论著 • 上一篇    下一篇

基于生产费用的柔性作业车间调度优化

刘晓霞;谢里阳;陶泽;郝长中;   

  1. 东北大学机械工程与自动化学院;东北大学机械工程与自动化学院;沈阳理工大学机械工程学院;沈阳理工大学机械工程学院 辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110168;辽宁沈阳110168
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2008-04-15 发布日期:2013-06-22
  • 通讯作者: Liu, X.-X.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(50275025)

Flexible job shop scheduling for decreasing production costs

Liu, Xiao-Xia (1); Xie, Li-Yang (1); Tao, Ze (2); Hao, Chang-Zhong (2)   

  1. (1) School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110004, China; (2) School of Mechanical Engineering, Shenyang Ligong University, Shenyang 110168, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2008-04-15 Published:2013-06-22
  • Contact: Liu, X.-X.
  • About author:-
  • Supported by:
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摘要： 考虑在制品库存费用、机床工时费、直接工人的工资费用、工件的提前和拖期完工造成的损失费用,提出了一种双资源柔性作业车间调度的生产费用计算方法.将模拟退火算法嵌入遗传算法中,设计了一种新的混合遗传算法.该算法首先利用遗传算法快速搜索一组较好的解,然后利用模拟退火算法进行群体寻优.采用基于工序的编码和一种新的解码方法,并运用多种交叉方法使得算法能够在解空间中尽可能地搜索最优解.为了避免最优解在进化过程中损失,采用择优操作将每代中的最优解保留下来,并不断更新.仿真结果表明:该方法是可行的,并具有一定的优越性.

关键词: 双资源, 柔性作业车间调度, 生产费用, 混合遗传算法

Abstract: Considering the inventory cost of workpieces in process, machining time cost, direct labor cost, inventory cost of early finished products and cost increment due to late finished products, a method calculating production cost of dual-resource(machine tool plus labor) flexible job shop scheduling is proposed. A new hybrid genetic algorithm is designed by embedding simulated annealing algorithm (SA) into genetic algorithm (GA), where GA is used to search for a group of better solutions to the problem of minimizing production cost and then SA is applied to searching them for the best one. Introducing an operation-based encoding and a new decoding method, several kinds of crossover operations are used to enable the algorithm to search the optimal solution in solvable space as far as possible. To avoid missing the optimal solution during the course of evolution, the optimized solution in every generation is kept then updated uninterruptedly. An example is given to prove that the scheduling method is feasible and efficient.

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