Accelerating the fireworks algorithm with an estimated convergence point

Jun Yu, Hideyuki Takagi, Ying Tan

    研究成果: 書籍/レポート タイプへの寄稿会議への寄与

    12 被引用数 (Scopus)

    抄録

    We propose an acceleration method for the fireworks algorithms which uses a convergence point for the population estimated from moving vectors between parent individuals and their sparks. To improve the accuracy of the estimated convergence point, we propose a new type of firework, the synthetic firework, to obtain the correct of the local/global optimum in its local area’s fitness landscape. The synthetic firework is calculated by the weighting moving vectors between a firework and each of its sparks. Then, they are used to estimate a convergence point which may replace the worst firework individual in the next generation. We design a controlled experiment for evaluating the proposed strategy and apply it to 20 CEC2013 benchmark functions of 2-dimensions (2-D), 10-D and 30-D with 30 trial runs each. The experimental results and the Wilcoxon signed-rank test confirm that the proposed method can significantly improve the performance of the canonical firework algorithm.

    本文言語英語
    ホスト出版物のタイトルAdvances in Swarm Intelligence - 9th International Conference, ICSI 2018, Proceedings
    編集者Ying Tan, Yuhui Shi, Qirong Tang
    出版社Springer Verlag
    ページ263-272
    ページ数10
    ISBN(印刷版)9783319938141
    DOI
    出版ステータス出版済み - 2018
    イベント9th International Conference on Swarm Intelligence, ICSI 2018 - Shanghai, 中国
    継続期間: 6月 17 20186月 22 2018

    出版物シリーズ

    名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    10941 LNCS
    ISSN(印刷版)0302-9743
    ISSN(電子版)1611-3349

    その他

    その他9th International Conference on Swarm Intelligence, ICSI 2018
    国/地域中国
    CityShanghai
    Period6/17/186/22/18

    !!!All Science Journal Classification (ASJC) codes

    • 理論的コンピュータサイエンス
    • コンピュータ サイエンス(全般)

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