Inertial geometric particle swarm optimization

Alberto Moraglio, Julian Togelius

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of a simplified form of traditional particle swarm optimization (PSO) without the inertia term that applies naturally to both continuous and combinatorial spaces. In this paper, we propose an extension of GPSO, the inertial GPSO (IGPSO), that generalizes the traditional PSO endowed with the full equation of motion of particles to generic search spaces. We then formally derive the specific IGPSO for the Hamming space associated with binary strings and present experimental results for this new algorithm.

    Original languageEnglish (US)
    Title of host publication2009 IEEE Congress on Evolutionary Computation, CEC 2009
    Pages1973-1980
    Number of pages8
    DOIs
    StatePublished - 2009
    Event2009 IEEE Congress on Evolutionary Computation, CEC 2009 - Trondheim, Norway
    Duration: May 18 2009May 21 2009

    Publication series

    Name2009 IEEE Congress on Evolutionary Computation, CEC 2009

    Other

    Other2009 IEEE Congress on Evolutionary Computation, CEC 2009
    CountryNorway
    CityTrondheim
    Period5/18/095/21/09

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computational Theory and Mathematics
    • Theoretical Computer Science

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  • Cite this

    Moraglio, A., & Togelius, J. (2009). Inertial geometric particle swarm optimization. In 2009 IEEE Congress on Evolutionary Computation, CEC 2009 (pp. 1973-1980). [4983182] (2009 IEEE Congress on Evolutionary Computation, CEC 2009). https://doi.org/10.1109/CEC.2009.4983182