• DocumentCode
    3215349
  • Title

    Sliced Particle Swarm Optimization (SPSO); A computationally efficient optimization technique

  • Author

    Garg, Harish ; Pattnaik, S.S. ; Devi, Swapna ; Bakwad, K.M. ; Panigrahi, B.K. ; Das, S.K.

  • Author_Institution
    Dept. of ETV & ECE, Nat. Inst. of Tech. Teachers´´ Training & Res., Chandigarh, India
  • fYear
    2009
  • fDate
    9-11 Dec. 2009
  • Firstpage
    61
  • Lastpage
    66
  • Abstract
    A new optimization technique named as sliced particle swarm optimization (SPSO) is proposed. It introduces the slicing of search space into rectangular slices. It gives complete solution in terms of reduction in the computational cost and tracking minutely each sliced search space. It introduces the momentum factor which restricts the particle in a sliced search space. Linearly decreasing inertia weight is applied throughout the computation process which balances between global exploration and local exploitation. The proposed algorithm is tested on three benchmark functions and the results are promising.
  • Keywords
    particle swarm optimisation; computational cost; computationally efficient optimization technique; global exploration; local exploitation; momentum factor; rectangular slices; search space; sliced particle swarm optimization; Acceleration; Benchmark testing; Computational efficiency; Convergence; Equations; Particle swarm optimization; Space technology; Stochastic processes; Sliced Particle Swarm Optimization (SPSO); Sliced best (S-best); momentum factor (mc);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-4244-5053-4
  • Type

    conf

  • DOI
    10.1109/NABIC.2009.5393601
  • Filename
    5393601