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Soft Computing

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09-04-2019 | Methodologies and Application

A core firework updating information guided dynamic fireworks algorithm for global optimization

Authors: Haitong Zhao, Changsheng Zhang, Jiaxu Ning

Published in: Soft Computing | Issue 2/2020

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Abstract

As a new variant of swarm intelligence algorithm, fireworks algorithm (FWA) exhibits promising performance on a wide set of optimization problems, for which the fireworks algorithm has been concentrated on and investigated by researchers recently. This paper aims to improve the performance of the FWA by exploiting updating information of the core firework to guide the algorithm’s searching process. Based on this mentality, this paper ameliorated the explosion strategy of core firework of dynamic fireworks algorithm (dynFWA). The proposed algorithm, named dynPgFWA in this paper, improved FWA from two aspects: amplifying the explosion amplitude on the direction on which core firework is updated, and making more sparks which are generated by core firework distributed on this direction to enhance the algorithm’s searching ability on updating direction. A numerical experiment on CEC2015 and CEC2017 test suite was implemented to verify the performance of the proposed algorithm. Results of the experiment indicated that dynPgFWA outperformed the compared evolutionary algorithms in the quality of solutions.

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Title: A core firework updating information guided dynamic fireworks algorithm for global optimization
Authors: Haitong Zhao
Changsheng Zhang
Jiaxu Ning
Publication date: 09-04-2019
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 2/2020
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-019-03953-0

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