A New Simple Micro-PSO for High Dimensional Optimization Problem

Abstract:

The particle swarm optimization (PSO) algorithm is a population-based intelligent stochastic search optimization technique, which has already been widely used to various of fields. In this paper, a simple micro-PSO is proposed for high dimensional optimization problem, which is resulted from being introduced escape boundary and perturbation for global optimum. The advantages of the simple micro-PSO are more simple and easily implemented than the previous micro-PSO. Experiments were conducted using Griewank, Rosenbrock, Ackley, Tablets functions. The experimental results demonstrate that the simple micro-PSO are higher optimization precision and faster convergence rate than PSO and robust for the dimension of the optimization problem.

• Periodical: Applied Mechanics and Materials (Volumes 236-237)
• Pages: 1195-1200
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.236-237.1195
• Online since: November 2012
• Authors: Wen Hua Han
• Keywords: Escape Boundary, Perturbation for Global Optimum, Simple Micro-PSO

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