A multi-agent system simulation based approach for collision avoidance in integrated Job-Shop Scheduling Problem with transportation tasks

被引:7
|
作者
Sanogo, Kader [1 ,6 ]
Benhafssa, Abdelkader Mekhalef [1 ]
Sahnoun, M'hammed [2 ]
Bettayeb, Belgacem [3 ]
Abderrahim, Moussa [4 ]
Bekrar, Abdelghani [5 ]
机构
[1] CESI LINEACT, EA 7527, Angouleme Campus, F-16400 La Couronne, France
[2] CESI LINEACT, EA 7527, Rouen Campus, F-76800 Rouen, France
[3] CESI LINEACT, EA 7527, Lille Campus, F-59800 Lille, France
[4] Univ Relizane, Relizane 48000, Algeria
[5] UPHF Campus Mont Houy, LAMIH, UMR CNRS 8201, F-59313 Valenciennes, France
[6] ENSAM, F-75013 Paris, France
关键词
!text type='JS']JS[!/text]SP; Transportation tasks; AGV; Simulation; Multi-agent system; Collision avoidance; OPTIMIZATION; ROBOTS;
D O I
10.1016/j.jmsy.2023.03.011
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
At the operational level of Flexible Manufacturing Systems (FMS), several research works have developed solutions not fully realizable considering the operational constraints, which can be difficult to model. One of the well-known problems in FMS is the Job-Shop Scheduling Problem (JSSP) with transportation tasks. Indeed, this problem is addressed by many researchers, but most of their studies do not consider operational constraints such as collision avoidance between transporters. Moreover, optimized scheduling may contain deadlock situations due to often neglected geometric constraints. Therefore, in this paper, we propose a simulation approach based on a multi-agent system to test the optimized results known in the literature in more realistic conditions, where collision avoidance between transporters is considered. We propose as well a sim-optimization approach to explore suitable solutions considering collision avoidance constraints. In addition, an algorithm is proposed to solve deadlocks. The obtained results highlight the impact of collision avoidance on the performance of the literature solutions while being more realistic. Furthermore, these results demonstrate the efficiency of the proposed algorithms, since all identified collisions are avoided and all deadlocks are also solved. The proposed approach is expected to be more attractive to the industries as it ensures a small gap between the theoretical and actual results.
引用
收藏
页码:209 / 226
页数:18
相关论文
共 50 条
  • [21] A simulated annealing algorithm for multi-agent systems: a job-shop scheduling application
    Aydin, ME
    Fogarty, TC
    [J]. JOURNAL OF INTELLIGENT MANUFACTURING, 2004, 15 (06) : 805 - 814
  • [22] A simulated annealing algorithm for multi-agent systems: A job-shop scheduling application
    Aydin, M. Emin
    Fogarty, Terence C.
    [J]. J Intell Manuf, 6 (805-814):
  • [23] A simulated annealing approach based simulation -optimisation to the dynamic job-shop scheduling problem
    Sel, Cagri
    Hamzadayi, Alper
    [J]. PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, 2018, 24 (04): : 665 - 674
  • [24] Multi-Agent modeling on scheduling of multi-variety and multi-process job-shop
    Chen, Yong
    Wu, Guo-Xian
    Lin, Fei-Long
    [J]. Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science), 2009, 43 (09): : 1672 - 1678
  • [25] Job Shop Dynamic Scheduling Model Based on Multi-Agent
    He, Li
    Liu, Yong-xian
    Xie, Hua-long
    Zhang, Yu
    [J]. 2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 829 - +
  • [26] A probabilistic approach to the Stochastic Job-Shop Scheduling problem
    Shoval, Shraga
    Efatmaneshnik, Mahmoud
    [J]. 15TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING, 2018, 21 : 533 - 540
  • [27] Dynamic Integration Mechanism for Job-Shop Scheduling Model Base Using Multi-Agent
    Niu Li
    Zhou Hong
    Han Xiaoting
    [J]. 2009 INTERNATIONAL CONFERENCE ON INFORMATION MANAGEMENT, INNOVATION MANAGEMENT AND INDUSTRIAL ENGINEERING, VOL 4, PROCEEDINGS, 2009, : 421 - 425
  • [28] Order-Controlled Production Employing Multi-Agent and Flexible Job-Shop Scheduling on a Physical Simulation Platform
    de Sousa, Alex Luiz
    de Oliveira, Andre Schneider
    [J]. 2022 LATIN AMERICAN ROBOTICS SYMPOSIUM (LARS), 2022 BRAZILIAN SYMPOSIUM ON ROBOTICS (SBR), AND 2022 WORKSHOP ON ROBOTICS IN EDUCATION (WRE), 2022, : 229 - 234
  • [29] Semi-autonomous Intersection Collision Avoidance through Job-shop Scheduling
    Ahn, Heejin
    Del Vecchio, Domitilla
    [J]. HSCC'16: PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON HYBRID SYSTEMS: COMPUTATION AND CONTROL, 2016, : 185 - 194
  • [30] A deep multi-agent reinforcement learning approach to solve dynamic job shop scheduling problem
    Liu, Renke
    Piplani, Rajesh
    Toro, Carlos
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2023, 159