The circular discrete particle swarm optimization algorithm for flow shop scheduling problem

被引:16
|
作者
Zhang, Jindong [1 ]
Zhang, Changsheng [1 ]
Liang, Shubin [2 ]
机构
[1] Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China
[2] Henan Normal Univ, Coll Comp Sci & Technol, Xinxiang 453007, Peoples R China
关键词
Flow shop scheduling; DPSO; Mutation; Particle similarity; HEURISTIC ALGORITHM; SEQUENCING PROBLEM;
D O I
10.1016/j.eswa.2010.02.024
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A circular discrete particle swarm optimization algorithm CDPSO is proposed to solve the flow shop scheduling problem with the objective of minimizing makespan. A particle similarity and swarm activity metric are defined. In order to preserve the diversity of the swarm, an order strategy is introduced. The threshold of the particle similarity changes adaptively with the swarm evolving degree. When the swarm activity is below a specified threshold, the obtained useful information is used to make the swarm evolve circularly. Furthermore, in order to improve the performance of CDPSO algorithm further, a neighborhood structure is defined and a neighborhood search strategy is proposed and introduced into it. Finally, the CDPSO algorithm is tested on different scale benchmarks and compared with the recently proposed efficient algorithms. The result shows that the solution quality and the stability of the CDPSO both precede the other two algorithms. It can be used to solve large scale flow shop scheduling problem. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:5827 / 5834
页数:8
相关论文
共 50 条
  • [41] Investigation of particle swarm optimization for job shop scheduling problem
    Liu, Zhixiong
    [J]. ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 3, PROCEEDINGS, 2007, : 799 - 803
  • [42] A discrete whale optimization algorithm for the no-wait flow shop scheduling problem
    Zhang, Sujun
    Gu, Xingsheng
    [J]. MEASUREMENT & CONTROL, 2023, 56 (9-10): : 1764 - 1779
  • [43] A particle swarm optimization algorithm for hybrid flow-shop scheduling with multiprocessor tasks
    Tseng, Chao-Tang
    Liao, Ching-Jong
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2008, 46 (17) : 4655 - 4670
  • [44] Hybrid particle swarm optimization for permutation flow shop scheduling
    Liu, Zhixiong
    Wang, Shaomei
    [J]. WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 3245 - +
  • [45] Scheduling of Flow Shop Production Systems with Particle Swarm Optimization
    Leguizamon, L. E.
    Leguizamon, L. A.
    Leguizamon, C. E.
    [J]. TECCIENCIA, 2021, 16 (31) : 1 - 13
  • [46] Job Shop Scheduling based on Improved Discrete Particle Swarm Optimization
    Yin, Lvjiang
    Yang, Lijun
    Hu, Mingmao
    [J]. PROCEEDINGS OF THE 21ST INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT 2014, 2015, : 99 - 101
  • [47] A discrete whale swarm algorithm for hybrid flow-shop scheduling problem with limited buffers
    Zhang, Chunjiang
    Tan, Jiawei
    Peng, Kunkun
    Gao, Liang
    Shen, Weiming
    Lian, Kunlei
    [J]. Robotics and Computer-Integrated Manufacturing, 2021, 68
  • [48] A discrete whale swarm algorithm for hybrid flow-shop scheduling problem with limited buffers
    Zhang, Chunjiang
    Tan, Jiawei
    Peng, Kunkun
    Gao, Liang
    Shen, Weiming
    Lian, Kunlei
    [J]. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2021, 68
  • [49] A Discrete Particle Swarm Optimization Algorithm With Adaptive Inertia Weight for Solving Multiobjective Flexible Job-shop Scheduling Problem
    Gu, Xiao-Lin
    Huang, Ming
    Liang, Xu
    [J]. IEEE ACCESS, 2020, 8 : 33125 - 33136
  • [50] A new algorithm for flexible job-shop scheduling problem based on particle swarm optimization
    Teekeng W.
    Thammano A.
    Unkaw P.
    Kiatwuthiamorn J.
    [J]. Artificial Life and Robotics, 2016, 21 (01) : 18 - 23