Introducing the Swingometer Crossover and Mutation Operators for FloatingPoint Encoded Genetic Algorithms

Shane Lee, Hefin Rowlands

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Genetic algorithms that utilise floating pointencoded chromosomes instead of the traditional binary or Gary code have become wide spread in recent years. This paper introduces new floatingpoint crossover and mutation operators for such genetic algorithms. The operators are derived from examining the implicit constraints that traditional binary crossover and mutation operators impose on the values of the parameters being affected. It is shown by an example that a genetic algorithm using these operators does converge and they should be considered for general use in floating-point genetic algorithms.
    Original languageEnglish
    Title of host publicationProceedings 19th European Conference on Modelling and Simulation
    EditorsYuri Merkuryev, Richard Zobel, Eugene Kerckhoffs
    PublisherECMS
    Number of pages5
    ISBN (Print)1-84233-112-4
    Publication statusPublished - 2005
    Event19th European Conference on Modelling and Simulation - Riga, Latvia
    Duration: 1 Jun 20054 Jun 2005

    Conference

    Conference19th European Conference on Modelling and Simulation
    Abbreviated titleECMS 2005
    Country/TerritoryLatvia
    CityRiga
    Period1/06/054/06/05

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