计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 211100193-6.doi: 10.11896/jsjkx.211100193

• 人工智能 • 上一篇    下一篇

急件订单插入下生产系统的重调度

黄鹏鹏, 赵春, 郭煜   

  1. 江西理工大学机电工程学院 江西 赣州 341000
  • 出版日期:2022-11-10 发布日期:2022-11-21
  • 通讯作者: 赵春(847852838@qq.com)
  • 作者简介:(hpp1261@126.com)

Rescheduling of Production System Under Interference of Emergency Order

HUANG Peng-peng, ZHAO Chun, GUO Yu   

  1. College of Mechanical and Electrical Engineering,Jiangxi University of Science and Technology,Ganzhou,Jiangxi 341000,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:HUANG Peng-peng,born in 1961,postgraduate,professor.His main research interests include lean manufacture and so on.
    ZHAO Chun,born in 1997,postgrad-duate.His main research interests include lean manufacture and so on.

摘要: 针对急件订单的扰动,对生产系统的重调度问题进行了研究。首先,根据产品工艺及所用设备计算急件订单与原有虚拟单元的相似度。然后,将相似的急件订单插入现有单元,调整生产资源调度方案,安排其优先生产。为了减小重调度对生产系统的冲击,兼顾生产的高效性与稳定性,构建以完成所有任务订单总流程时间及产品工序次序扰动最小为目标的数学模型,设计一个遗传-蚁群算法,借助遗传算法求得较优解后,再利用蚁群算法的正反馈求解问题。最后,将实例代入所建模型,借助MATLAB编程求解。实验结果表明,该方法能够优化重调度的生产资源分配,保证企业生产的效率与稳定。

关键词: 急件订单, 重调度, 虚拟单元, 遗传-蚁群算法

Abstract: The rescheduling of all orders is investigated after the insertion of emergency order into the mixed-flow production system.First,according to the product’s technology and equipments used,the similarity between the emergency order and the original virtual cells is calculated.Similar rush orders are then inserted into existing cells and the production resource scheduling scheme is adjusted to prioritise the production of rush orders.In order to reduce the impact of rescheduling on the production system and take into account the efficiency and stability of production,a mathematical model is constructed with the goal of minimizing the total process time and product sequence disturbance for all task orders,and a genetic-ant colony algorithm is designed to solve the problem with the positive feedback of the ant colony algorithm after finding a better solution by the genetic algorithm.Finally,an example is substituted into the constructed model and solved with the help of MATLAB programming.The results show that the method could optimize the allocation of production resources for rescheduling and ensure the efficiency and stability of enterprise production.

Key words: Emergency order, Rescheduling, Virtual cells, Genetic-ant colony algorithm

中图分类号: 

  • TP301
[1]WEIRT,JEVAKUMAR V.A class of nonconvex functions and mathematical programming[J].Bulletin of the Australian Mathe-matical Society,1988,38(2):177-189.
[2]YIN Y Q,CHENG T,WANG D J.Rescheduling on identicalparallel machines with machine disruptions to minimize total completion time[J].European Journal of Operational Research,2016,252(3):737-749.
[3]WANG C,JIANG P Y.Manifold learning based rescheduling decision mechanism for recessive distur-bances in RFID-driven job shops[J].Journal of Intelligent Manufacturing,2018,29(7):1485-1500.
[4]SALIDO M A,ESCAMILLA J,BARBER F,et al.Rescheduling in job-shop problems for sustainable manufacturing systems[J].Journal of Cleaner Production,2016,162(S).
[5]LIU Z,ZHANG Z M,DU X J.Rescheduling Decision Method of Manufacturing Shop Based on Improved TOPSIS[J].Modular Machine Tool & Auto-matic Manufacturing Technique,2017(1):157-160.
[6]WLTER J,MEHTA F D,RAO X.Aiding vehicle Schedulingand rescheduling using Machine Learning[J].International Journal of Transport Development and Integration,2020,4(4):308-320.
[7]ZHANG G H,LU X X,HU Y F,et al.Machine break-down rescheduling of flexible job shop based on improved imperialist competitive algorithm[J].Journal of Computer Applications,2021,41(8):2242-2248.
[8]XU L Y,CHENG Z,MI H,et al.Molding Machines Batch Rescheduling Optimization Based on Improved Variable Neighborhood Search[J].Jounal of Tongji University,2020,48(10):1460-1469.
[9]CHEN T.Virtual Cellular Rescheduling Considering Lot Splitting under Interference of Emergency Orders[D].Zhenjiang:Jiangsu University of Science and Technology,2017.
[10]HAN W M,CHEN T,GAO L L,et al.Virtual Cellular Rescheduling under Interference of Emergency Order[J].Operations Research and Management Science,2018,27(2):68-78.
[11]YAN J G,XING L N,ZHANG Z S,et al.Dual Time Window Constrained Job-shop Scheduling Algorithm[J].Science Technology and Engineering,2016,16(26):85-92.
[12]GUO Y,ZHU B,CHE Z Z,et al.Workshop Scheduling Prototype System Based on Improved Genetic Algorithm[J].Science Technology and Engineering,2020,20(5):1940-1946.
[13]SONG M S,HUANG J,ZHANG S P,et al.The Research on the Dimensionless Criterion and Methods about the Design of Multi-index Orthogonal Experiment[J].Industrial Engineering and Management,2014,19(1):41-46.
[14]OUYANG S,SHI Y L.A New Improved Entropy Method and Its Application in Power Quality Evaluation[J].Automation of Electric Power Systems,2013,37(21):156-159.
[15]KESEN S E,DAS S K,GUNGR Z.A genetic algorithm based heuristic for scheduling of virtual manufacturing cells(VMCs)[J].Computers & Operations Research,2010,37(6):1148-1156.
[16]QIAO Z,HERVE M,MANIER M.A modified shifting bottleneck heuristic and disjunctive graph for job shop scheduling problems with transportation constraints[J].International Journal of Production Research,2014,52(4):985-1002.
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