基于子群极值和Sharing重分布的粒子群优化算法

为提高粒子群优化算法在优化问题中的效率，提出了粒子群优化算法(ESPSO)。其基本思想是分多子群搜索和Sharing函数重分布。主要工作包括:(1)将粒子群分成多个子群，各自搜索解空间;(2)信息共享机制中引入子群极值，使粒子更新能参考其他粒子的信息;(3)使用Sharing对陷入局部最优的粒子进行重分布。在4个基准函数上的优化实验表明，新方法比经典的IPPSO粒子群算法在达到目标精度的成功率上提高了64%~93%.

Particle Swarm Optimization Algorithm Based on Extreme Value of Sub-swarm and Sharing Redistribution

To improve the efficiency of Particle Swarm Optimization, this paper proposed a novel Particle Swarm Optimization algorithm(ESPSO). The basic idea is Sub-Swarm mechanism and Sharing Redistribution. The main contribudons include, (1) Divides whole Swarm into n sulrSwarm; Each sub-Swarm search solution Independently; (2) Introduces extreme value of Sub-Swarm strategies to enable particle interaction; (3) Introduces Sharing Function to redistribute some Particle. The experiments on four benchmark functions show that the new algorithm increases success rate by 64%~93% compared with IPPSO.