DocumentCode
2219975
Title
Exponentially decreased dimension number strategy based dynamic search fireworks algorithm for solving CEC2015 competition problems
Author
Zheng, Shaoqiu ; Yu, Chao ; Li, Junzhi ; Tan, Ying
Author_Institution
Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, P.R. China
fYear
2015
fDate
25-28 May 2015
Firstpage
1083
Lastpage
1090
Abstract
Fireworks algorithm (FWA) is one swarm intelligence algorithm proposed in 2010, which takes the inspiration from the firework explosion process. Compared with other meta-heuristic algorithms, FWA presents a cooperative explosive search manner. In the explosive search manner, the explosion amplitudes, explosion sparks´ numbers and explosion dimension selection methods play the key roles for its successful implementation. In this paper, the performance analyses of the different explosion dimension number strategies in FWA and its variants are presented at first, then the exponentially decreased explosion dimension number strategy is introduced for the most recent dynamic search fireworks algorithm (dynFWA), called ed-dynFWA, to enhance its local search ability. To validate the performance of ed-dynFWA, it is used to participate in the CEC 2015 competition for solving learning based optimization problems.
Keywords
Algorithm design and analysis; Explosives; Heuristic algorithms; Optimization; Silicon; Sparks;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location
Sendai, Japan
Type
conf
DOI
10.1109/CEC.2015.7257010
Filename
7257010
Link To Document