Election Campaign Algorithm for Multimodal Function Optimization

Author

Lv, Wenge ; Xie, Qinghua ; Liu, Zhiyong ; Zhang, Xiangwei ; Luo, Shaoming ; Cheng, Siyuan

Author_Institution

Fac. of Electro-Mech. Eng., Guangdong Univ. of Technol., Guangzhou, China

Volume

2

fYear

2010

fDate

28-31 May 2010

Firstpage

157

Lastpage

161

Abstract

In this paper, we present a new algorithm named Election campaign algorithm (ECA) for the multimodal function optimization. It acts by simulating the behavior that the election candidates pursue the highest support in election campaign. The proposed approaches are validated using test functions taken from the specialized literature, and our results are compared with those obtained by genetic algorithm (GA) and particle swarm optimization algorithm (PSO). Our comparative study indicates that ECA verifies its good performance when dealing with multimodal functions.

Keywords

genetic algorithms; particle swarm optimisation; politics; election campaign algorithm; genetic algorithm; multimodal function optimization; particle swarm optimization algorithm; test functions; Benchmark testing; Design for experiments; Distribution functions; Genetic algorithms; Humans; Nominations and elections; Particle swarm optimization; Probability; Sampling methods; Statistical analysis; election campaign algorithm; multimodal function;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Science and Optimization (CSO), 2010 Third International Joint Conference on

Conference_Location

Huangshan, Anhui

Print_ISBN

978-1-4244-6812-6

Electronic_ISBN

978-1-4244-6813-3

Type

conf

DOI

10.1109/CSO.2010.152

Filename

5533067