• DocumentCode
    3024527
  • Title

    Based on Tabu Search and Particle Swarm Optimization Algorithms Solving Job Shop Scheduling Optimization Problems

  • Author

    Liang Xu ; Li Yanpeng ; Jiao Xuan

  • Author_Institution
    Software Technol. Inst., Dalian Jiaotong Univ., Dalian, China
  • fYear
    2013
  • fDate
    29-30 June 2013
  • Firstpage
    322
  • Lastpage
    324
  • Abstract
    Solving the Job shop Scheduling problem, the design is based on Particle Swarm Optimization and Taboo Search which is a fast algorithm, And in this algorithm, bring in particle swarm strategy and taboo search strategy, A hybrid intelligence algorithm based on Particle Swarm algorithm and the taboo Search algorithm(TS-PSO) is designed. It overcomes particle swarm optimization algorithm in solving combinatorial optimization problem, and better to avoid the tabu search algorithm falling into local optimum, and convergence speed has also been increased. Through particle swarm and taboo search algorithm combined, the results show that this algorithm has very good accuracy of convergence, and is feasible, and compared with the traditional scheduling algorithm, Embodies the obvious superiority.
  • Keywords
    combinatorial mathematics; convergence; job shop scheduling; particle swarm optimisation; search problems; TS-PSO; combinatorial optimization problem; convergence speed; hybrid intelligence algorithm design; job shop scheduling optimization problem; local optimum; particle swarm optimization algorithm; particle swarm strategy; taboo search algorithm; taboo search strategy; Algorithm design and analysis; Convergence; Job shop scheduling; Optimization; Particle swarm optimization; Search problems; Standards; Hybrid scheduling; Job Shop Scheduling Problem; Particle Swarm Optimization; Taboo Search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Manufacturing and Automation (ICDMA), 2013 Fourth International Conference on
  • Conference_Location
    Qingdao
  • Type

    conf

  • DOI
    10.1109/ICDMA.2013.78
  • Filename
    6597997