Fireworks Algorithm for Optimization

Inspired by observing fireworks explosion, a novel swarm intelligence algorithm, called Fireworks Algorithm (FA), is proposed for global optimization of complex functions. In the proposed FA, two types of explosion (search) processes are employed, and the mechanisms for keeping diversity of sparks a...

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Bibliographic Details
Published inAdvances in Swarm Intelligence pp. 355 - 364
Main Authors Tan, Ying, Zhu, Yuanchun
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
fireworks algorithm
function optimization
natural computing
particle swarm optimization
swarm intelligence
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Summary:Inspired by observing fireworks explosion, a novel swarm intelligence algorithm, called Fireworks Algorithm (FA), is proposed for global optimization of complex functions. In the proposed FA, two types of explosion (search) processes are employed, and the mechanisms for keeping diversity of sparks are also well designed. In order to demonstrate the validation of the FA, a number of experiments were conducted on nine benchmark test functions to compare the FA with two variants of particle swarm optimization (PSO) algorithms, namely Standard PSO and Clonal PSO. It turns out from the results that the proposed FA clearly outperforms the two variants of the PSOs in both convergence speed and global solution accuracy.
ISBN:3642134947
9783642134944
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-13495-1_44