A Hybrid Leader Cooperation Algorithm for high dimention numerical optimization

Author

Peng, Sheng ; Li, Yuanxiang

Author_Institution

State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China

fYear

2011

fDate

8-10 Aug. 2011

Firstpage

4514

Lastpage

4517

Abstract

A new improve Swarm Intelligence Algorithm which is named Hybrid Leader Cooperation Algorithm (HLCA) is proposed in this paper. The HLCA first separates the individuals by its rank. According to its rank, if the individual is a good one then cooperation with the others by conservation of the momentum operator; else it studied from the rest individuals and the leader for searching. Finally, the numerical experiments results show that the HLCA is better than the PSO and the Multi-Parent Evolutionary Algorithm (MPEA). The HLCA not only can avoid to the local optimal but also accelerate the convergence rate.

Keywords

artificial intelligence; convergence of numerical methods; evolutionary computation; particle swarm optimisation; HLCA; MPEA; PSO; convergence rate; high dimention numerical optimization; hybrid leader cooperation algorithm; improve swarm intelligence algorithm; momentum operator; multiparent evolutionary algorithm; Acceleration; Algorithm design and analysis; Biology; Convergence; Particle swarm optimization; Software algorithms; Leader Cooperation; Swarm Intelligence Algorithm; The Conservation of the momentum;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on

Conference_Location

Deng Leng

Print_ISBN

978-1-4577-0535-9

Type

conf

DOI

10.1109/AIMSEC.2011.6010252

Filename

6010252