An empirical study on influence of approximation approaches on enhancing fireworks algorithm

This paper presents an empirical study on the influence of approximation approaches on accelerating the fireworks algorithm search by elite strategy. In this study, we use three sampling data methods to approximate fitness landscape, i.e. the best fitness sampling method, the sampling distance near...

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Bibliographic Details
Published in2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC) pp. 1322 - 1327
Main Authors Yan Pei, Shaoqiu Zheng, Ying Tan, Takagi, Hideyuki
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
Subjects
Acceleration
Approximation
Approximation algorithms
Benchmark testing
Elite Strategy
Fireworks Algorithm
Fitness Landscape
Least squares approximation
Sampling methods
Sparks
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Summary:This paper presents an empirical study on the influence of approximation approaches on accelerating the fireworks algorithm search by elite strategy. In this study, we use three sampling data methods to approximate fitness landscape, i.e. the best fitness sampling method, the sampling distance near the best fitness individual sampling method and the random sampling method. For each approximation methods, we conduct a series of combinative evaluations with the different sampling method and sampling number for accelerating fireworks algorithm. The experimental evaluations on benchmark functions show that this elite strategy can enhance the fireworks algorithm search capability effectively. We also analyze and discuss the related issues on the influence of approximation model, sampling method, and sampling number on the fireworks algorithm acceleration performance.
ISBN:9781467317139
1467317136
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2012.6377916