Labeled-GA with adaptive mutation rate

Pitoyo Hartono, Shuji Hashimoto, Mattias Wahde

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

    2 Citations (Scopus)

    Abstract

    In this paper we propose a modified GA that assigns a unique mutation rate to each gene based on the contribution of the respective gene's contribution to the fitness of the individual. Although the proposed model is not "parameter free", through a number of experiments, we show that the parameters for this model are significantly insensitive to the landscape of the problems compared with the mutation rate in conventional GA, implying that this model could deal effectively with a wide range of problems the requirement to set the mutation rate empirically.

    Original languageEnglish
    Title of host publicationProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
    Pages1851-1858
    Number of pages8
    Volume2
    Publication statusPublished - 2004
    EventProceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR
    Duration: 2004 Jun 192004 Jun 23

    Other

    OtherProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
    CityPortland, OR
    Period04/6/1904/6/23

      Fingerprint

    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Hartono, P., Hashimoto, S., & Wahde, M. (2004). Labeled-GA with adaptive mutation rate. In Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 (Vol. 2, pp. 1851-1858)