Migrational GA that preserves solutions in non-static optimization problems

Pitoyo Hartono*, Shuji Hashimoto

*この研究の対応する著者

    研究成果: Conference contribution

    2 被引用数 (Scopus)

    抄録

    GA has been successfully introduced to solve various optimizations problems. One of the characteristics of GA is that once it has converged, most of its population members will be copies of the best individual, causing GA to loose population diversity. This characteristic is a setback when we consider non-stationary problems in which the fitness functions vary with time. In this paper we propose Migrational-GA that stores the past environmental solutions and retrieved them rapidly when that environment is reactivated, through probabilistic operation.

    本文言語English
    ホスト出版物のタイトルProceedings of the IEEE International Conference on Systems, Man and Cybernetics
    ページ255-260
    ページ数6
    1
    出版ステータスPublished - 2001
    イベント2001 IEEE International Conference on Systems, Man and Cybernetics - Tucson, AZ, United States
    継続期間: 2001 10 72001 10 10

    Other

    Other2001 IEEE International Conference on Systems, Man and Cybernetics
    国/地域United States
    CityTucson, AZ
    Period01/10/701/10/10

    ASJC Scopus subject areas

    • ハードウェアとアーキテクチャ
    • 制御およびシステム工学

    引用スタイル