Molding Machines Batch Rescheduling Optimization Based on Improved Variable Neighborhood Search
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1.School of Mechanical Engineering, Tongji University, Shanghai 200092, China;2.Zhejiang Quzhou Lianzhou Refrigerant Co., Ltd., Quzhou 324000, China

Clc Number:

TH186

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    Abstract:

    This paper proposed a batch rescheduling method based on improved variable neighborhood search algorithm for two types of events which were molding machine failure and early delivery, and the orders were batch-divided based on the minimum batching principle and non-equal batching principle. Then, a rescheduling mathematical model was established considering the process stability and punctuality. After that, an improved variable neighborhood search algorithm was designed, which had a faster convergence speed and a stronger global optimization ability by constructing transition neighborhood and superposition neighborhood. Finally, a magnetic material molding workshop is taken as an example to verify the results. The results show that the proposed rescheduling method can ensure on-time delivery of order, raise the utilization rate of molding machine, and provide a reference for the production decision of factory.

    Reference
    [1] 李亚峰. 磁性材料行业现状与发展前景分析[J]. 新材料产业, 2018(7):51.
    [2] CHENG M, MUKHERJEE N J, SARIN S C. A review of lot streaming[J]. International Journal of Production Research, 2013, 51(23/24):7023.
    [3] 王海燕, 王万良, 黄风立, 等. 分批优化调度问题综述及面向节能研究展望[J]. 计算机集成制造系统, 2017, 23(3):542.
    [4] LOW C, HSU C M, HUANG K I. Benefits of lot splitting in job-shop scheduling[J]. The International Journal of Advanced Manufacturing Technology, 2004, 24(9/10): 773.
    [5] SHIM S O, KIM Y D. A branch and bound algorithm for an identical parallel machine scheduling problem with a job splitting property[J]. Computers and Operations Research, 2008, 35(3):863.
    [6] TAHAR D N, YALAOUI F, CHU C, et al. A linear programming approach for identical parallel machine scheduling with job splitting and sequence-dependent setup times[J]. International Journal of Production Economics, 2006, 99(1/2):63.
    [7] 史青涛. 基于遗传算法的单工序并行机分批调度研究[D]. 大连:大连理工大学, 2014.
    [8] 张震, 尤凤翔, 赵欣桥. 有模具约束的并行机批量流调度问题研究[J]. 工业工程, 2018, 21(3):59.
    [9] 李国臣, 乔非, 王俊凯, 等. 考虑能耗约束的并行机组批调度[J]. 中南大学学报(自然科学版), 2017, 48(8):2063.
    [10] 王海燕. 基于混合差分进化算法的制造过程分批优化调度研究[D]. 杭州:浙江工业大学, 2011.
    [11] LARSEN R, PRANZO M. A framework for dynamic rescheduling problems[J]. International Journal of Production Research, 2018. DOI:10.1080/00207543.2018.1456700.
    [12] GAO K, YANG F, ZHOU M C, et al. Flexible job-shop rescheduling for new job insertion by using discrete Jaya algorithm[J]. IEEE Transactions on Cybernetics, 2018 (99):1.
    [13] 顾泽平, 杨建军, 周勇. 不确定因素扰动下多目标柔性作业车间鲁棒调度方法[J]. 计算机集成制造系统, 2017, 23(1): 66.
    [14] LI X, PENG Z, DU B, et al. Hybrid artificial bee colony algorithm with a rescheduling strategy for solving flexible job shop scheduling problems[J]. Computers & Industrial Engineering, 2017, 113: 10.
    [15] 俞胜平, 柴天佑. 开工时间延迟下的炼钢-连铸生产重调度方法[J]. 自动化学报, 2016, 42(3): 358.
    [16] MAO K, PAN Q K, PANG X, et al. An effective Lagrangian relaxation approach for rescheduling a steelmaking-continuous casting process[J]. Control Engineering Practice, 2014, 30(9):67.
    [17] 屈新怀, 刘栋, 丁必荣. 柔性作业车间分批调度的多样性可控粒子群优化算法[J]. 计算机辅助设计与图形学学报, 2014, 26(1):121.
    [18] 唐秋华, 陈世杰, 赵萌, 等. 机器故障下加工车间优化重调度方式预测[J]. 中国机械工程, 2019, 30(2):188.
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XU Liyun, CHENG Zan, MI Hong, LI Aiping. Molding Machines Batch Rescheduling Optimization Based on Improved Variable Neighborhood Search[J].同济大学学报(自然科学版),2020,48(10):1460~1469

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History
  • Received:October 08,2019
  • Online: November 04,2020
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