Journal of Shandong University(Engineering Science) ›› 2021, Vol. 51 ›› Issue (4): 17-23.doi: 10.6040/j.issn.1672-3961.0.2021.091

Previous Articles     Next Articles

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

PDF (PC)

486

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

CLC Number: 

  • TP391
[1] LEE J, BAGHERI B, KAO H A. A cyber-physical systems architecture for industry 4.0-based manufacturing systems[J]. Manufacturing Letters, 2015, 3:18-23.
[2] J IANG J R. An improved cyber-physical systems architecture for industry 4.0 smart factories[J]. Advances in Mechanical Engineering, 2018, 10(6): 1-15.
[3] ZHANG J, DING G, ZOU Y, et al. Review of job shop scheduling research and its new perspectives under industry 4.0[J]. Journal of Intelligent Manufacturing, 2019, 30(4):1809-1830.
[4] WU R, GUO S, LI Y, et al. Improved artificial bee colony algorithm for distributed and flexible job-shop scheduling problem[J]. Control and Decision, 2019, 34(12):2527-2536.
[5] ZHANG F, MEI Y, NGUYEN S, et al. Evolving scheduling heuristics via genetic programming with feature selection in dynamic flexible job-shop scheduling[J]. IEEE Transactions on Cybernetics, 2021, 51(4):1797-1811.
[6] MENG T, PAN Q, SANG H. A hybrid artificial bee colony algorithm for a flexible job shop scheduling problem with overlapping in operations[J]. International Journal of Production Research, 2018, 56(16): 5278-5292.
[7] WU X, LI J, SHEN X, et al. A nsga-III for solving dynamic flexible job shop scheduling problem considering deterioration effect[J]. IET Collaborative Intelligent Manufacturing, 2020, 2(4):22-33.
[8] LUO S. Dynamic scheduling for flexible job shop with new job insertions by deep reinforcement learning[J]. Applied Soft Computing, 2020, 91(21):1-17.
[9] ZADEH M S, KATEBI Y, DONIAVI A. A heuristic model for dynamic flexible job shop scheduling problem considering variable processing times[J]. International Journal of Production Research, 2019, 57(910):3020-3035.
[10] ZHANG M, TAO F, NEE A Y C. Digital twin enhanced dynamic job-shop scheduling[J]. Journal of Manufacturing Systems, 2021, 58(B): 146-156.
[11] FANGY, PENG C, LOU P, et al. Digital-twin-based job shop scheduling toward smart manufacturing[J]. IEEE Transactions on Industrial Informatics, 2019, 15(12):6425-6435.
[12] CHAUDHRY I A, KHAN A A. A research survey: review of flexible job shop scheduling techniques[J]. International Transactions in Operational Research, 2015, 23(3):551-591.
[13] LIU S, YANG Y, ZHOU Y. A swarm intelligence algorithm-lion swarm optimization[J]. Pattern Recognition and Artificial Intelligence, 2018, 31(5): 431-441.
[14] LIU Q, ZHANG C, RAO Y, et al. Flexible job-shop scheduling problem with improved genetic algorithm[J]. Industrial Engineering and Management, 2009, 14(2):59-66.
[15] WEI Y. Research on improved particle swarm and its application in flexible job shop scheduling[D]. Lanzhou: School of Computer and Communication, Lanzhou University of Technology, 2020.
[16] ZHANG D, JIANG M. Parallel discrete lion swarm optimization algorithm for solving traveling salesman problem[J]. Journal of Systems Engineering and Electronics, 2020, 31(4):751-760.
[17] TAO F, ZHANG M. Digital win -floor: A New shop-floor paradigm towards smart manufacturing[J]. IEEE Access, 2017, 5:20418-20427.
[18] BRANDIMARTE P. Routing and scheduling in a flexible job shop by tabu search[J]. Annals of Operations Research, 1993, 41(3):157-183.
[19] PEZZELLA F, MORGANTI G, CIASCHETTI G. A genetic algorithm for the Flexible Job-shop Scheduling Problem[J]. Computers & Operations Research, 2008, 35(10):3202-3212.
[20] GIRISH B S, JAWAHAR N. A Particle Swarm Optimization algorithm for Flexible Job shop scheduling problem[C] //Proceeding of 5th Annual IEEE International Conference on Automation Science and Engineering. Banfalore, India: IEEE, 2009: 298-303.
[1] SHAO Mengwei, YUAN Shifei, ZHOU Hongzhi, WANG Naihua. Optimisation of finned tube structure based on BP neural network and genetic algorithm [J]. Journal of Shandong University(Engineering Science), 2025, 55(6): 76-82.
[2] LI Xiaohui, LIU Xiaofei, SUN Weitong, ZHAO Yi, DONG Yuan, JIN Yinli. An inspection task assignment and path planning algorithm based on vehicles-UAVs collaboration [J]. Journal of Shandong University(Engineering Science), 2025, 55(5): 101-109.
[3] WEN Yujie, ZHANG Damin. Enhanced beluga whale optimization algorithm and its application [J]. Journal of Shandong University(Engineering Science), 2025, 55(3): 88-99.
[4] ZHU Ming, SHI Chenglong, LÜ Pan, LIU Xianrong, SUN Chi, CHEN Jiancheng, FAN Hongyun. Deformation prediction method and engineering application of deep foundation pit based on optimized LSTM method [J]. Journal of Shandong University(Engineering Science), 2025, 55(3): 141-148.
[5] YAN Renwu, LIN Jianxiong, LI Peiqiang, WU Guoyao, KUANG Yu. Bi-level optimization strategy for active distribution networks considering carbon emission factors and dynamic reconfiguration [J]. Journal of Shandong University(Engineering Science), 2025, 55(2): 16-27.
[6] ZHENG Fangyuan, CHEN Lizheng, WANG Wenkui, ZHANG Hanyuan, FAN Yingle. Intelligent building energy optimization considering user satisfaction [J]. Journal of Shandong University(Engineering Science), 2025, 55(2): 45-57.
[7] PENG Zhenhua, WANG Zhechao, LI Jiajia, QIAO Liping, ZHAO Qinni, LI Hanshuo. Evaluation of containment properties and optimization design of water curtain system for an extended underground oil storage cavern [J]. Journal of Shandong University(Engineering Science), 2025, 55(2): 125-133.
[8] Xiuguang SONG,Xinming GUO,Fang YAN,Guoqiang LI,Yuan TIAN. Intelligent scheduling technology of highway emergency rescue vehicle [J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 1-17.
[9] Haoyuan LI,Jingming YU,Guilin ZHANG,Bin ZHANG. Optimization of manufacturing parameters for optical fiber preform core based on intelligent algorithm [J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 149-156.
[10] Caihui LIU,Qi ZHOU,Xiaowen YE. An intrusion detection model based on improved ReliefF algorithm [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 1-10.
[11] Shaowei YU,Ruiling QIN,Jingjing GUAN,Can JI,Shuo FENG,Rui JIANG,Yingning LIU. Eco-driving model for connected and automated vehicle platoons using the traffic capacity remainder [J]. Journal of Shandong University(Engineering Science), 2022, 52(6): 23-29.
[12] Xuhao WANG,Qianqian LIU,Hucheng LI,cheng LI,Peng LI,Yifeng LING. Research and optimization of hollow form of precast concrete pavement slab [J]. Journal of Shandong University(Engineering Science), 2022, 52(4): 139-150.
[13] Ruiyi YAN,Zhen DONG,Sen LU,Yanhua LAI,Mingxin LÜ. Analysis of the influence of the underside baffle and deflector of the fume hood on the flow field [J]. Journal of Shandong University(Engineering Science), 2021, 51(5): 122-130.
[14] DING Fei, JIANG Mingyan. Housing price prediction based on improved lion swarm algorithm and BP neural network model [J]. Journal of Shandong University(Engineering Science), 2021, 51(4): 8-16.
[15] GONG Weiping, GUAN Hongjun, LI Hongwei, LIU Jieben, SHI Yuetao. Optimization of heating load distribution of combined unit based on EBSILON simulation software [J]. Journal of Shandong University(Engineering Science), 2021, 51(4): 77-83.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] WANG Su-yu,<\sup>,AI Xing<\sup>,ZHAO Jun<\sup>,LI Zuo-li<\sup>,LIU Zeng-wen<\sup> . Milling force prediction model for highspeed end milling 3Cr2Mo steel[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 1 -5 .
[2] LI Kan . Empolder and implement of the embedded weld control system[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(4): 37 -41 .
[3] SHI Lai-shun,WAN Zhong-yi . Synthesis and performance evaluation of a novel betaine-type asphalt emulsifier[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(4): 112 -115 .
[4] KONG Xiang-zhen,LIU Yan-jun,WANG Yong,ZHAO Xiu-hua . Compensation and simulation for the deadband of the pneumatic proportional valve[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 99 -102 .
[5] CHEN Rui, LI Hongwei, TIAN Jing. The relationship between the number of magnetic poles and the bearing capacity of radial magnetic bearing[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(2): 81 -85 .
[6] LI Ke,LIU Chang-chun,LI Tong-lei . Medical registration approach using improved maximization of mutual information[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 107 -110 .
[7] JI Tao,GAO Xu/sup>,SUN Tong-jing,XUE Yong-duan/sup>,XU Bing-yin/sup> . Characteristic analysis of fault generated traveling waves in 10 Kv automatic blocking and continuous power transmission lines[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 111 -116 .
[8] . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 27 -32 .
[9] WANG Li-ju,HUANG Qi-cheng,WANG Zhao-xu . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(6): 51 -56 .
[10] SUN Dianzhu, ZHU Changzhi, LI Yanrui. [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 84 -86 .
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd