郑州大学学报（理学版）2016，Vol.48Issue(3)：75-81,7.DOI:10.13705/j.issn.1671-6841.2016022
一种拟随机初始化模拟退火粒子群算法
A Quasi-randomized Initialized Simulated Annealing Particle Swarm Optimization Algorithm
摘要
Abstract
To overcome the shortcomings of particle swarm optimization ( PSO) algorithm such as prema-ture convergence and stagnation when solving the high-dimensional problems, a quasi-randomized simula-ted annealing ( SA)-PSO algorithm was proposed. The performance of algorithm in high-dimensional opti-mization space could be improved by using the Hammersley initialization. And the idea of SA algorithm was introduced into the PSO algorithm, combining with the fast searching ability of PSO and the probabi-listic jumping property of SA, to jump out of local optimal algorithm to achieve the global optimum. The proposed algorithm could effectively overcome the stagnation phenomenon, enhance the global search ability in high-dimensional space. The proposed algorithm was then tested on 5 different functions, and the results demonstrated better optimization ability over the traditional PSO algorithm.关键词
拟随机序列/初始化/模拟退火/粒子群优化Key words
quasi-random sequence/initialization/simulated annealing/particle swarm optimization分类
信息技术与安全科学引用本文复制引用
王杰,李慧慧,彭金柱..一种拟随机初始化模拟退火粒子群算法[J].郑州大学学报（理学版）,2016,48(3):75-81,7.基金项目
教育部高等学校博士学科点专项科研基金资助项目(20124101120001) （20124101120001）
河南省教育厅科学技术研究重点项目(14A413009) （14A413009）
中国博士后科学基金资助项目(2014T70685) （2014T70685）
