基于子群极值和Sharing重分布的粒子群优化算法

计算机科学 ›› 2010, Vol. 37 ›› Issue (12): 224-226.

基于子群极值和Sharing重分布的粒子群优化算法

龚燕,张浩

(绵阳电业局绵阳621000)

出版日期:2018-12-01 发布日期:2018-12-01
基金资助:
本文受川电科技(【2010】45号)资助。

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

GONG Yan,ZHANG Hao

Online:2018-12-01 Published:2018-12-01

摘要/Abstract

摘要： 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%.

关键词: 粒子群算法，子群，极值，Sharing

Abstract: 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.

Key words: PSO, Sub-swarm, Extreme value, Sharing

龚燕,张浩. 基于子群极值和Sharing重分布的粒子群优化算法[J]. 计算机科学, 2010, 37(12): 224-226. https://doi.org/

GONG Yan,ZHANG Hao. Particle Swarm Optimization Algorithm Based on Extreme Value of Sub-swarm and Sharing Redistribution[J]. Computer Science, 2010, 37(12): 224-226. https://doi.org/

参考文献

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed