一种新的改进粒子群算法

A new improved Particle swarm optimization algorithm

本文给出构造了一种根据适度聚度和空间位置聚度自适应动态调整的惯性权重,并在算法中对全局最优解进行变异。数值实验证明改进后的粒子群算法的性能优于带线性递减权重的粒子群算法。

The paper constructs an adaptive inertia weight by fitness value aggregation degree and space position aggregation degree so as to produce dynamically changing inertia weight,at the same takes mutation strategy to global optimization.It is shown by tested with well-known benchmark functions that improved algorithm is better than PSO algorithms with linearly decreasing weight.