Abstract
Particle Swarm Optimization (PSO) is one of new optimization methods. PSO is a powerful method to find the minimum of a numerical function on a continuous definition domain. However, it has been pointed out that the performance of PSO on large-scale problems is not always satisfactory. In this paper, we study a new computational model to improve the performance on large-scale optimization problems.
