Authors: Dai-lin Yuan, Qiu Chen
Addresses: School of Mechanics and Engineering; School of Mathematics, Southwest Jiaotong University, Chengdu, 610031, P.R. China. ' School of Mechanics and Engineering, Southwest Jiaotong University, Chengdu, 610031, P.R. China
Abstract: In order to improve the performance of particle swarm optimisation algorithm in the complicated function optimisation, a new improved measure was advanced. The new algorithm only memorised the individual information of finite steps in the iterations and utilised the average information of swarm. Due to the individuals forgetting the former best positions, the forgetting character was hold. The ability of exploration was improved because of using forgetting character and average information of swarm. The simulations of complicated function optimisation show that the new algorithm can find the global best solution more easily than the common particle swarm optimisation algorithm.
Keywords: particle swarm optimisation; PSO; forgetting character; function optimisation.
International Journal of Bio-Inspired Computation, 2010 Vol.2 No.1, pp.59 - 64
Available online: 03 Dec 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article