• DocumentCode
    515244
  • Title

    A dynamic multipoint detecting PSO

  • Author

    Yong, Wang ; Xing, Pang

  • Author_Institution
    Coll. of Math. & Comput. Sci., Guangxi Univ. for Nat., Nanning, China
  • Volume
    1
  • fYear
    2010
  • fDate
    9-10 Jan. 2010
  • Firstpage
    474
  • Lastpage
    479
  • Abstract
    The chief aim of the present work is to propose a particle swarm optimization(PSO) by using a dynamic multipoint exploring approach. The main technique of this algorithm is that in the preceding phase of the algorithm, every particle can choose its searching direction and its moving velocity independently not being restricted or attracted by the optimal position of which have found by the parcle swarm and makes use of a dynamic multipoint random detecting method. It indicatess, from the empirical results of four typical benchmark functions´ optimization, that the optimization algorithm has the performance of rapid convergence rate, high accurate numerical solution, good stability and powerful robust. This proves that the algorithm is a promising means in solving the complex function optimization problems.
  • Keywords
    convergence; particle swarm optimisation; benchmark function optimization; dynamic multipoint exploring approach; dynamic multipoint random detecting method; particle swarm optimization; rapid convergence rate; Convergence of numerical methods; Educational institutions; Genetic mutations; Heuristic algorithms; Mathematics; Numerical stability; Particle swarm optimization; Phase detection; Robust stability; Velocity control; Algorithm; Dynamic Explore; Multipoint Detection; Particle Swarm Optimization (PSO);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Logistics Systems and Intelligent Management, 2010 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-7331-1
  • Type

    conf

  • DOI
    10.1109/ICLSIM.2010.5461379
  • Filename
    5461379