华东交通大学学报Issue(3)：44-49,6.
一种基于邻域空间的混合粒子群优化算法
Hybrid Particle Swarm Optimization Based on Neighborhood Space
摘要
Abstract
Considering the information sharing deficiency of standard particle swarm optimization,this paper proposes a hybrid particle swarm optimization based on neighborhood space which modifies the updating equa-tion for particle velocity by embedding pattern search algorithm into the particle swarm. The experimental study of four typical test functions demonstrates the suggested algorithm has accomplished the balance between global“exploration”and local“exploitation”by taking advantage of the local search power of pattern search and the global optimum capacity of particle swarm algorithm based on neighborhood space. The study also shows that the suggested algorithm is especially applicable to optimizing high-dimensional multimodal func-tions with the characteristics of high precision and strong robustness.关键词
邻域空间/模式搜索算法/粒子群优化算法Key words
neighborhood space/pattern search algorithm/PSO分类
信息技术与安全科学引用本文复制引用
..一种基于邻域空间的混合粒子群优化算法[J].华东交通大学学报,2013,(3):44-49,6.基金项目
国家自然科学基金项目（11161021）；华东交通大学科学基金项目 （）
