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计算机系统应用:2020,29(6):241-246
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带机器人制造单元的作业车间调度仿真
(长安大学 电子与控制工程学院, 西安 710064)
Hybrid Meta-Heuristic Scheme to Solve Robotic Cell Job-Shop Scheduling Problem
(School of Electronics and Control Engineering, Chang’an Universicty, Xi’an 710064, China)
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投稿时间:2019-10-22    修订日期:2019-11-20
中文摘要: 针对带有机器人制造单元的作业车间调度优化问题, 在若干加工机器上可以加工具有特定加工工序的若干工件, 并且搬运机器人可以将工件在装卸载站与各加工机器间进行搬运. 在实际生产过程中, 由于不确定性, 特别是带有存货的加工单元, 要求工件的完工时间在一个时间窗内, 而不是一个特定的时间点. 因此针对此情况的作业车间, 考虑到其在求解问题过程中的复杂性和约束性等特点, 研究了在时间窗约束下, 目标值为最小化工件完成时间提前量和延迟量的总权重. 提出了一种将文化基因算法与邻域搜索技术(变邻域下降搜索)相结合的改进元启发式算法, 在求得最优目标值的同时, 可得到最优值的工件加工序列及机器人搬运序列. 通过实验结果表明, 所提出的算法有效且优于传统文化基因算法与遗传算法.
Abstract:To solve the job-shop scheduling optimization problem with robotic cell, several jobs with specific processing operations can be processed on several processing machines, and the handling robot can carry the jobs between the loading/unloading stations and the processing machines. In the real world, due to the uncertainty, especially the processing unit with inventory, the completion time of the job is required in a time window, rather than a specific time point. Therefore, considering the complexity and constraints of the job-shop with robotic cell, the objective is to minimize the total weighted earliness and tardiness. An improved meta-heuristic algorithm is proposed, which combines memetic algorithm with local search technology (variable neighborhood descent). The optimal job processing order and robot handling sequence can be obtained simultaneously. Computational experiments show that the proposed algorithm is more efficient than other algorithms.
文章编号:7423     中图分类号:    文献标志码:
基金项目:陕西省自然科学基金(2018JM5165); 中央高校基本科研业务费专项资金(310832173701); 西安市科技项目(201805045YD23CG29)
引用文本:
李晓辉,杨晰,赵毅.带机器人制造单元的作业车间调度仿真.计算机系统应用,2020,29(6):241-246
LI Xiao-Hui,YANG Xi,ZHAO Yi.Hybrid Meta-Heuristic Scheme to Solve Robotic Cell Job-Shop Scheduling Problem.COMPUTER SYSTEMS APPLICATIONS,2020,29(6):241-246

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