Particle swarm optimization method in multiobjective problems
Proceedings of the 2002 ACM symposium on Applied computing
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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.