The fl exi-PSO: Towards a more fl exible particle swarm optimizer

Muhammad Kathrada

    Research output: Contribution to journalArticle

    Abstract

    This paper presents some simple heuristics to increase fl exibility in particle swarms. The particle velocities are updated with an extended inertia weight formulation, particles are also allowed to act as hill-climbers and the population is divided into exploration particles which are allowed to roam the search space more freely and exploitation particles which try to improve the fi tness by fi ne tuning a local search, thus making the swarm much more fl exible in its behavior. These heuristics improve the traditional inertia weight PSO and show comparable performance in the computational results of benchmark functions to other state of the art techniques. The benchmark functions used are a rigorous test bed for evaluating any optimization algorithm. An introduction and general overview of approaches to particle swarm optimizers is fi rst presented, followed by a discussion of the proposed method. The result of the experiments is then discussed followed by proposals for future research directions. © Operational Research Society of India.

    Original languageEnglish
    Pages (from-to)52-68
    Number of pages17
    JournalOPSEARCH
    Volume46
    Issue number1
    DOIs
    Publication statusPublished - Mar 2009

    Keywords

    • Exploitation
    • Exploration
    • Extended particle swarm
    • Heuristics
    • Hill-climber

    Fingerprint Dive into the research topics of 'The fl exi-PSO: Towards a more fl exible particle swarm optimizer'. Together they form a unique fingerprint.

  • Cite this