信息与控制2017，Vol.46Issue(6)：677-684,8.DOI:10.13976/j.cnki.xk.2017.0677
一种基于种群多样性的粒子群优化算法设计及应用
Design and Application of Particle Swarm Optimization Algorithm Based on Population Diversity
摘要
Abstract
To overcome the premature convergence and low searching accuracy of the particle swarm optimization (PSO) algorithm,we propose a population diversity-based particle swarm optimization algorithm (PDPSO).First,we introduce the nonlinear characteristics of particles by the population diversity to describe the distribution state in the searching process.Second,we develop an adaptive inertia weight adjustment strategy to balance the global exploration ability and the local exploitation ability based on the population diversity of particles.Finally,we test the performance of PDPSO by using the standard test functions.We use the proposed PDPSO algorithm to optimize the energy consumption of the wastewater treatment process.Unlike the standard PSO algorithm and other improved PSO algorithms,the proposed PDPSO algorithm can avoid being trapped in the local optimum and achieve high accuracy,as demonstrated by simulation results.The proposed PDPSO algorithm can optimize the wastewater treatment process to reduce energy consumption within effluent water qualities.关键词
种群多样性/自适应惯性权重/粒子群优化算法/污水处理运行能耗Key words
population diversity/adaptive inertia weight/particle swarm optimization algorithm/energy consumption in the wastewater treatment process分类
信息技术与安全科学引用本文复制引用
韩红桂,卢薇,乔俊飞..一种基于种群多样性的粒子群优化算法设计及应用[J].信息与控制,2017,46(6):677-684,8.基金项目
国家自然科学基金资助项目(61622301,61533002) （61622301,61533002）
中国博士后科学基金资助项目(2014M550017) （2014M550017）
教育部博士点基金资助项目(20131103110016) （20131103110016）
北京市教育委员会项目(km201410005001,KZ201410005002) （km201410005001,KZ201410005002）
