The research base on memetic meta-heuristic Shuffled Frog-Leaping Algorithm

Author

Yue, Mei ; Hu, Tao ; Guo, Baoping ; Guo, Xuan

Author_Institution

Key Lab. of Optoelectron. Devices & Syst. of Minist. of Educ. & Guangdong Province, Shenzhen Univ., Shenzhen, China

Volume

3

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

117

Lastpage

120

Abstract

Shuffled frog-leaping algorithm (SFLA) is a new meta-heuristic population evolutionary algorithm. Shuffled frog-leaping algorithm has fast and excellent global exploration capability. Firstly, the paper introduces the principle of SFLA. Then, the paper analyses the parameters of SFLA. By the examination, the paper validates the effect of parameters to SFLA. The paper compares SFLA with genetic algorithm (GA) and particle swarm optimization (PSO) by the testing function. we can find SFLA is better than GA and PSO in astringency and the global search capability.

Keywords

evolutionary computation; optimisation; randomised algorithms; search problems; global exploration capability; global search capability; memetic metaheuristic shuffled frog-leaping algorithm; metaheuristic cooperative random algorithm; metaheuristic population evolutionary algorithm; Convergence; Evolutionary computation; Genetic algorithms; Genetic engineering; Intelligent transportation systems; Laboratories; Optoelectronic devices; Particle swarm optimization; Power electronics; Testing; genetic algorithm; memetic meta-heuristic; particle swarm optimization; shuffled frog-leaping algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics and Intelligent Transportation System (PEITS), 2009 2nd International Conference on

Conference_Location

Shenzhen

Print_ISBN

978-1-4244-4544-8

Type

conf

DOI

10.1109/PEITS.2009.5406809

Filename

5406809