Authors: Ji-Shan Fan
Addresses: School of Electronic Engineering, HuaiHai Institute of Technology, 59 Cangwu Road, Lianyungang 222005, Jiangsu Province, China
Abstract: A number of researchers have effectively applied particle swarm optimisation (PSO) to multi-objective optimisation problems. However, it is important to obtain a well-converged and well-distributed set of Pareto-optimal solutions. This paper proposes a multi-region particle swarm optimisation (MRPSO) algorithm for multi-objective optimisation. The proposed algorithm utilises multiple regions to make its capability of global optimisation more readily and avoid being trapped in local optimum. The denoising performance of MRPSO algorithm is measured using emulation according to five well-known test functions. The results of emulation experiments indicate that the performance of MRPSO algorithm is a competitive method in the terms of convergence near the Pareto-optimal front, and it will become an effective approach for solving multi-objective optimisation problems.
Keywords: multi-objective optimisation; multi-region PSO; particle swarm optimisation; multi-region strategy.
International Journal of Computer Applications in Technology, 2012 Vol.44 No.2, pp.117 - 123
Published online: 23 Aug 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article