计算机应用研究2012，Vol.29Issue(12)：4448-4450,3.DOI:10.3969/j.issn.1001-3695.2012.12.010
基于模拟退火的自适应粒子群优化算法的改进策略
Strategy of adaptive simulated annealing particle swarm optimization algorithm
摘要
Abstract
In PSO algorithm, it tends to suffer from premature convergence and slow rate of convergence on solving the problem of optimization problems. This paper proposed a new algorithm about initialization and simulated annealing algorithm combined with the PSO for function optimization. It divided the new method into two phases. In order to improve the convergence rate, pre-standard optimization algorithm, and post ideas on the use of simulated annealing to optimize the parameters of PSO for searching the optimum. It applied eight classic unimodal/multimodal function. Compared with other algorithms, the simulation results show that the algorithm avoids the premature convergence phenomenon, enhanced the convergence rate and improves the performance of global optimization.关键词
粒子群优化算法/模拟退火/函数优化Key words
particle swarm optimization algorithm/ simulated annealing/ function optimization分类
信息技术与安全科学引用本文复制引用
于海平,刘会超,吴志健..基于模拟退火的自适应粒子群优化算法的改进策略[J].计算机应用研究,2012,29(12):4448-4450,3.基金项目
国家自然科学基金资助项目(61070008) （61070008）
河南省重点科技攻关资助项目(112102210383) （112102210383）
