New Adaptive Particle Swarm Optimization Algorithm with Dynamically Changing Inertia Weight
一种动态改变惯性权重的自适应粒子群算法

A new adaptive Particle Swarm Optimization algorithm with dynamically changing inertia weight(DCWPSO)was presented to solve the problem that the linearly decreasing weight(LDWPSO)of the Particle Swarm Optimization algorithm cannot adapt to the complex and nonlinear optimization process.The rate of cluster focus distance changing was introduced in this new algorithm and the weight was formulated as a function of this factor according to its impact on the search performance of the swarm.In each iteration proc...