New Particle Swarm Optimization Variant with Modified Neighborhood Structure

DOI
  • Meng Ang Koon
    Faculty of Engineering, Technology and Built Environment, UCSI University
  • Mohamad Juhari Mohd Rizon
    Faculty of Engineering, Technology and Built Environment, UCSI University
  • Cheng Wy-Liang
    Faculty of Engineering, Technology and Built Environment, UCSI University
  • Hong Lim Wei
    Faculty of Engineering, Technology and Built Environment, UCSI University
  • Sun Tiang Sew
    Faculty of Engineering, Technology and Built Environment, UCSI University
  • Hong Wong Chin
    Maynooth International Engineering College, Fuzhou University
  • Rahman Hameedur
    Maynooth International Engineering College, Fuzhou University
  • Pan Li
    Faculty of Engineering, Technology and Built Environment, UCSI University

Description

Numerous particle swarm optimization (PSO) variants were proposed in past decades to tackle different types optimization problems more robustly. Nevertheless, the imbalance of explorative and exploitative search behaviors remains as an on-going research challenge that can restrict the performance of PSO. In this paper, a new variant known as PSO with time-varying topology connectivity (PSO-TVTC) is proposed. A time-varying topology connectivity (TVTC) module is designed to achieve the proper regulation on explorative and exploitative behaviors of PSO via dynamic modifications of particle's topology connectivity throughout the optimization process. Experimental results reveal that the proposed PSO-TVTC has exhibited prominent performance among its competitors by producing 7 best mean fitness out of 8 benchmark functions.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390291767548321152
  • DOI
    10.5954/icarob.2022.os22-4
  • ISSN
    21887829
  • Text Lang
    en
  • Data Source
    • JaLC
    • Crossref
  • Abstract License Flag
    Disallowed

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