• DocumentCode
    130854
  • Title

    The research of parallel multi-objective particle swarm optimization algorithm

  • Author

    Wu Jian ; Tang XinHua ; Cao Yong

  • Author_Institution
    Dept. of Inf. Sci. & Technol., Shandong Univ. of Political Sci. & Law, Jinan, China
  • fYear
    2014
  • fDate
    27-29 June 2014
  • Firstpage
    300
  • Lastpage
    304
  • Abstract
    The shortcomings of traditional serial algorithm on the multi-objective optimization problems are well known for its long computation time and the slow convergence rate, especially when we have complicated computation and large amount of data. To conquer these shortcomings, we propose a parallel multi-objective particle swarm optimization algorithm. Through analyzing the mechanism of multi-objective particle swarm optimization algorithm, we introduced the parallel mechanism into the multi-objective particle swarm algorithm, and realized a parallel multi-objective particle swarm algorithm based on the model of the island. We apply our algorithm on the knapsack problem as an illustration, and find the solving efficiency of the multi-objective problems improves evidently.
  • Keywords
    knapsack problems; particle swarm optimisation; knapsack problem; multiobjective particle swarm optimization algorithm; parallel mechanism; Algorithm design and analysis; Clustering algorithms; Convergence; Optimization; Particle swarm optimization; Sociology; Statistics; multi-objective optimization; parallel; particle swarm algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2327-0586
  • Print_ISBN
    978-1-4799-3278-8
  • Type

    conf

  • DOI
    10.1109/ICSESS.2014.6933568
  • Filename
    6933568