A Cellular Genetic Algorithm with Disturbances: Optimisation Using Dynamic Spatial Interactions

Michael Kirley

    Research output: Contribution to journalArticle

    32 Citations (Scopus)

    Abstract

    This paper describes a novel evolutionary algorithm inspired by the nature of spatial interactions in ecological systems. The Cellular Genetic Algorithm with Disturbances (CGAD) can be seen as a hybrid between a fine-grained and a coarse-grained parallel genetic algorithm. The introduction of a ldquodisturbance-colonisationrdquo cycle provides a mechanism for maintaining flexible subpopulation sizes and self-adaptive controls on migration. Experiments conducted, using a range of stationary and non-stationary optimisation problems, show how changes in the structure of the environment can lead to changes in selective pressure, population diversity and subsequently solution quality. The significance of the disturbance events lies in the new ldquoecologicalrdquo patterns that arise during the recovery phase.
    Original languageEnglish
    Pages (from-to)321-342
    Number of pages22
    JournalJournal of Heuristics
    Volume8
    Issue number3
    DOIs
    Publication statusPublished - 2002

    Fingerprint Dive into the research topics of 'A Cellular Genetic Algorithm with Disturbances: Optimisation Using Dynamic Spatial Interactions'. Together they form a unique fingerprint.

  • Cite this