基于分组型法的粒子群优化算法

A New Particle Swarm Optimization Algorithm Based on Grouping

粒子群优化算法近年来受到许多科学家的关注,被广泛地使用。因为粒子群优化算法具有搜索速度快、效率高、算法简单、可调参数少等特点。但是粒子群算法也存在着很明显的问题,在高维复杂的优化问题中,有可能会陷入局部最小点而无法跳出,从而无法得到全局最优值。针对粒子群优化算法在寻找最优解的过程中存在的问题,依据公司自上而下的金字塔型的管理模式提出了分组型的粒子群优化算法试图解决这些存在的问题,并且借助5个基准测试函数对提出的分组型的粒子群优化算法进行了仿真测试,验证了该算法的有效性。

In view of the problems existing in the process of finding the optimal solution of particle swarm optimization algorithm,a group-based particle swarm optimization algorithm is proposed to solve these problems according to the topdown pyramid management model of the company,and the group-based particle swarm optimization algorithm proposed in this paper is simulated by five benchmarks test,and verify the effectiveness of the algorithm.