Title :
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
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;
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
DOI :
10.1109/AIMSEC.2011.6010252
