Accelerating fireworks algorithm with weight-based guiding sparks

Yuhao Li, 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

    6 被引用数 (Scopus)


    We introduce two strategies into the guided fireworks algorithm (GFWA) to further improve its performance by generating one or more weight-based guiding spark individual(s) for each firework individual. The first strategy assigns different weights to spark individuals under each firework individual according to their fitness and then calculates one or more guiding vector(s) to guide the firework individual to evolve into potential directions. The second strategy decides the number of weight-based guiding spark individuals dynamically based on the evolution of a firework individual, i.e. if a firework individual does not evolve and survive in the next generation, then the second strategy reduces the number of spark individuals generated around the firework individual and generates the same reduced number of weight-based guiding spark individuals additionally. We design a controlled experiment to evaluate the performance of our proposal using CEC 2013 benchmark functions with five different dimensions. The experiment results confirm that the proposed strategies can provide effective guidance information to improve the GFWA performance significantly, and its acceleration effect for higher dimensional tasks is more obvious.

    ホスト出版物のタイトルAdvances in Swarm Intelligence - 10th International Conference, ICSI 2019, Proceedings
    編集者Ying Tan, Yuhui Shi, Ben Niu
    出版社Springer Verlag
    出版ステータス出版済み - 2019
    イベント10th International Conference on Swarm Intelligence, ICSI 2019 - Chiang Mai, タイ
    継続期間: 7月 26 20197月 30 2019


    名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    11655 LNCS


    会議10th International Conference on Swarm Intelligence, ICSI 2019
    CityChiang Mai

    !!!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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