• DocumentCode
    3462034
  • Title

    New Particle Swarm Optimization Algorithm for Makespan Minimization in Permutation Flowshop Sequencing

  • Author

    Chen, Ting-Yu ; Chen, Chuen-Lung

  • Author_Institution
    Dept. of Manage. Inf. Syst., Nat. Chengchi Univ., Taipei, Taiwan
  • fYear
    2009
  • fDate
    7-9 Dec. 2009
  • Firstpage
    868
  • Lastpage
    871
  • Abstract
    Particle Swarm Optimization (PSO) is a new type of heuristic inspired by the flocking behavior of birds. This paper presents a Particle Swarm Optimization (PSO) to solve the permutation flowshop scheduling problem (PFSP) objectives, to minimize the makespan. To this end, we have proposed the use of discrete PSO algorithm for the position of the smallest value (SPV) to use a random key representation of Bean [Baena Bean, Genetic algorithms and random keys sequencing and optimization, Orsa calculated Journal 6 (2) ( 1994) 154-160]. In the proposed algorithm, the particle and the velocity re-defined and effective way to develop a series of new particles. In addition, we analyzed the characteristics of the elite jobs in the proposed algorithm. The results showed that the idea really follows the approach of PSO.
  • Keywords
    flow shop scheduling; particle swarm optimisation; particle swarm optimization; permutation flowshop scheduling problem; random key representation; smallest value position; Acceleration; Algorithm design and analysis; Birds; Control systems; Equations; Genetic algorithms; Genetic programming; Management information systems; Minimization methods; Particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
  • Conference_Location
    Kaohsiung
  • Print_ISBN
    978-1-4244-5543-0
  • Type

    conf

  • DOI
    10.1109/ICICIC.2009.278
  • Filename
    5412652