Towards computing the parameters of the simple genetic algorithm

Jacek Malec, Roger Jonsson

    Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

    Abstract

    The problem of finding appropriate probabilities for crossover and mutation with respect to resampling may be addressed using the Markov chain model. Our efforts in this direction lead through a simplification of the mixing matrix incorporating both probabilities. We present the simplification and discuss some of its ramifications. We expect that it may lead to some improvement of the computational properties of the Markov chain model of the simple genetic algorithm.
    Original languageEnglish
    Title of host publicationProceedings of the 2001 Congress on Evolutionary Computation
    PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
    Pages516-520
    Volume1
    ISBN (Print)0-7803-6657-3
    DOIs
    Publication statusPublished - 2001
    EventCEC2001, Congress on Evolutionary Computation - Seoul, Korea, Republic of
    Duration: 2001 May 272001 May 31

    Publication series

    Name
    Volume1

    Conference

    ConferenceCEC2001, Congress on Evolutionary Computation
    Country/TerritoryKorea, Republic of
    CitySeoul
    Period2001/05/272001/05/31

    Subject classification (UKÄ)

    • Computer Science

    Free keywords

    • mutation probability
    • genetic algorithms
    • crossover probability
    • Markov processes
    • mixing matrix
    • probability
    • Markov chain model
    • simple genetic algorithm

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