Improved Particle Swarm Optimizer Based on Nonlinear Inertia Weight Dynamic Changing
基于惯性权重非线性动态变化的微粒群算法

This paper proposes a particle swarm optimizer (PSO) with nonlinear inertia weight dynamic changing (NDPSO) to improve the speed of convergence and fine tune the search in the multidimensional space. The decreasing exponent of inertia weight is selected by the region which particle stays in the swarm and each particle will be having different inertia weight according to the place which it stays. If the particle is far from the optimal point of the swarm the exponent of inertia weight will be smaller in orde...