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山东大学学报 (工学版) ›› 2021, Vol. 51 ›› Issue (4): 17-23.doi: 10.6040/j.issn.1672-3961.0.2021.091

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基于狮群算法的数字孪生车间调度问题优化

黄澄1,2,袁东风1,2*,张海霞2,3   

  1. 1.山东大学信息科学与工程学院, 山东 青岛 266237;2.山东省无线通信技术重点实验室, 山东 济南 250100;3.山东大学控制科学与工程学院, 山东 济南 250061
  • 发布日期:2021-08-18
  • 作者简介:黄澄(1997— ),女,江苏镇江人,硕士研究生,主要研究方向为智能算法,人工智能. E-mail:hc970608@163.com. *通信作者简介:袁东风(1958— ),男,四川安岳人,教授,博士,主要研究方向为智能通信系统,移动边缘计算和云计算,人工智能和通信大数据处理. E-mail:dfyuan@sdu.edu.cn
  • 基金资助:
    山东省重点研发计划重大科技创新工程课题资助项目(2019TSLH0202,2019JZZY01011)

Optimization of digital twin job scheduling problem based on lion swarm algorithm

HUANG Cheng1,2, YUAN Dongfeng1,2*, ZHANG Haixia2,3   

  1. 1. School of Information Science and Engineering, Shandong University, Qingdao 266237, Shandong, China;
    2. Shandong Provincial Key Laboratory of Wireless Communication Technologies, Jinan 250100, Shandong, China;
    3. School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China
  • Published:2021-08-18

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摘要： 针对柔性作业车间调度问题,提出一种基于狮群算法的数字孪生柔性作业车间调度方法。基于实际生产过程的需求,使用狮群算法生成柔性作业车间调度初始方案,建立物理车间与虚拟车间实时交互的数字孪生柔性作业车间调度模型,在搭建的虚拟车间中对初始调度方案根据设备利用率进行方案优化。采用数字孪生模型解决设备故障等车间突发事件对生产进程的影响问题。通过使用真实车间数据对机加工车间生产调度过程试验,结果表明,采用狮群算法求解柔性作业车间调度问题,搜寻能力强,搜索速度快,可以在不同规模的问题中找到更优的解决方案;狮群算法结合数字孪生的柔性作业车间调度方案能够整体优化系统性能,有效处理扰动带来的延长生产时间问题。

关键词: 柔性作业车间调度, 数字孪生, 狮群算法, 优化, 最大完工时间

Abstract: A digital twin job shop scheduling method based on lion swarm optimization algorithm was proposed aiming at the flexible job shop scheduling problem, which could effectively improve the utilization of equipment and solve the production delay caused by dynamic factors such as equipment failure in discrete manufacturing. The lion swarm optimization algorithm was used to generate the initial scheme based on the requirements of the actual production process. A digital twin flexible job shop scheduling model with real-time interaction between physical shop floor and virtual shop floor was established. The initial scheduling scheme was optimized according to the equipment utilization in the virtual shop floor. The digital twin model was used to solve the delay of production process caused by shop floor emergency such as equipment failure. By using real workshop data to test the machine tool production scheduling process in machining workshop, the results showed that the flexible job shop scheduling problem based on lion swarm optimization algorithm had strong search ability and fast search speed, and could find better solutions in different scale problems. The flexible job shop scheduling scheme with digital twin could optimize the system performance as a whole, and effectively deal with the problem of prolonging production time caused by disturbance.

Key words: flexible job shop scheduling, digital twin, lion swarm algorithm, optimization, makespan

中图分类号: 

  • TP391
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