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
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;
Conference_Titel :
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location :
Sendai, Japan
DOI :
10.1109/CEC.2015.7257010