Accelerating fireworks algorithm with weight-based guiding sparks

Yuhao Li, Jun Yu, Hideyuki Takagi, Ying Tan

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

    6 Citations (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.

    Original languageEnglish
    Title of host publicationAdvances in Swarm Intelligence - 10th International Conference, ICSI 2019, Proceedings
    EditorsYing Tan, Yuhui Shi, Ben Niu
    PublisherSpringer Verlag
    Number of pages10
    ISBN (Print)9783030263683
    Publication statusPublished - 2019
    Event10th International Conference on Swarm Intelligence, ICSI 2019 - Chiang Mai, Thailand
    Duration: Jul 26 2019Jul 30 2019

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11655 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference10th International Conference on Swarm Intelligence, ICSI 2019
    CityChiang Mai

    All Science Journal Classification (ASJC) codes

    • Theoretical Computer Science
    • Computer Science(all)


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