计算机应用研究2011，Vol.28Issue(8)：2828-2830,3.DOI:10.3969/j.issn.1001-3695.2011.08.007
一种引入密度因子的改进粒子群优化算法
Improved particle swarm optimization algorithm with density factor
摘要
Abstract
Based on the conventional linear decreased weight particle swarm optimization algorithm, proposed a novel improved PSO with a so-called density factors involved. Defined the density of one generation in the form of radial basis function with the average fitness value and the best one of the whole swarm, which was used as a metric of the assembling degree around the best fitness value. In the process of evolution, introduced a disturbing term in the LDW factor formula when the density factor was larger than a particular constant in order to scatter the particle swarm and leap the local minimum. The simulation tests show that the new PSO algorithm avoids the premature phenomenon in a sense especially for high dimensional and multiple extremum scenarios.关键词
粒子群优化/密度因子/线性递减惯性权重Key words
particle swarm optimization (PSO) / density factor/ linear decreased inertia weight分类
信息技术与安全科学引用本文复制引用
孙锋利,何明一,高全华..一种引入密度因子的改进粒子群优化算法[J].计算机应用研究,2011,28(8):2828-2830,3.基金项目
国家自然科学基金资助项目(60736007):长安大学中央高校专项科研基金资助项目(CHD2010JC133) （60736007）
