Flexible job-shop scheduling/rescheduling in dynamic environment: a hybrid MAS/ACO approach

被引:67
|
作者
Zhang, Sicheng [1 ]
Wong, Tak Nam [2 ]
机构
[1] Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing, Peoples R China
[2] Univ Hong Kong, Dept Ind & Mfg Syst, Hong Kong, Hong Kong, Peoples R China
关键词
dynamic scheduling; multi-agent systems; ant colony optimisation; flexible job-shop; job-shop scheduling; MULTIAGENT SYSTEM; OPTIMIZATION; ALGORITHM; INTEGRATION; MODEL;
D O I
10.1080/00207543.2016.1267414
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In real-world manufacturing, disruptions are often encountered during the execution of a predetermined schedule, leading to the degradation of its optimality and feasibility. This study presents a hybrid approach for flexible job-shop scheduling/rescheduling problems under dynamic environment. The approach, coined as HMA' is a combination of multi-agent system (MAS) negotiation and ant colony optimisation (ACO). A fully distributed MAS structure has been constructed to support the solution-finding process by negotiation among the agents. The features of ACO are introduced into the negotiation mechanism in order to improve the performance of the schedule. Experimental studies have been carried out to evaluate the performance of the approach for scheduling and rescheduling under different types of disruptions. Different rescheduling policies are compared and discussed. The results have shown that the proposed approach is a competitive method for flexible job-shop scheduling/rescheduling for both schedule optimality and computation efficiency.
引用
收藏
页码:3173 / 3196
页数:24
相关论文
共 50 条
  • [21] A two-stage hybrid algorithm for flexible job-shop scheduling
    Gao Li
    Xu Ke-lin
    Zhu Wei
    Yang Na-na
    COMPUTATIONAL MATERIALS SCIENCE, PTS 1-3, 2011, 268-270 : 476 - 481
  • [22] Towards Energy Efficient Scheduling and Rescheduling for Dynamic Flexible Job Shop Problem
    Nouiri, M.
    Bekrar, A.
    Trentesaux, D.
    IFAC PAPERSONLINE, 2018, 51 (11): : 1275 - 1280
  • [23] A genetic algorithm for flexible job-shop scheduling
    Chen, HX
    Ihlow, J
    Lehmann, C
    ICRA '99: IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-4, PROCEEDINGS, 1999, : 1120 - 1125
  • [24] Flexible Job-Shop Scheduling with Changeover Priorities
    Milne, Holden
    Adesina, Opeyemi
    Campbell, Russell
    Friesen, Barbara
    Khawaja, Masud
    MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE (LOD 2021), PT I, 2022, 13163 : 611 - 625
  • [25] SCHEDULING RULES FOR A SMALL DYNAMIC JOB-SHOP: A SIMULATION APPROACH
    Dileepan, P.
    Ahmadi, M.
    INTERNATIONAL JOURNAL OF SIMULATION MODELLING, 2010, 9 (04) : 173 - 183
  • [26] A novel dynamic scheduling strategy for solving flexible job-shop problems
    Tao Ning
    Ming Huang
    Xu Liang
    Hua Jin
    Journal of Ambient Intelligence and Humanized Computing, 2016, 7 : 721 - 729
  • [27] A novel dynamic scheduling strategy for solving flexible job-shop problems
    Ning, Tao
    Huang, Ming
    Liang, Xu
    Jin, Hua
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2016, 7 (05) : 721 - 729
  • [28] A KNOWLEDGE-BASED APPROACH TO DYNAMIC JOB-SHOP SCHEDULING
    FARHOODI, F
    INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 1990, 3 (02) : 84 - 95
  • [29] Greedy randomized adaptive search for dynamic flexible job-shop scheduling
    Baykasoglu, Adil
    Madenoglu, Fatma S.
    Hamzadayi, Alper
    JOURNAL OF MANUFACTURING SYSTEMS, 2020, 56 (56) : 425 - 451
  • [30] Genetic algorithm for flexible job-shop scheduling
    Univ of Magdeburg, Magdeburg, Germany
    Proc IEEE Int Conf Rob Autom, (1120-1125):