| 一种改进粒子群优化算法及其在投资规划中的应用 |
| |
| 引用本文： | 刘羿,陈增强,袁著址.一种改进粒子群优化算法及其在投资规划中的应用[J].数学的实践与认识,2007,37(11):82-87. |
| |
| 作者姓名： | 刘羿 陈增强 袁著址 |
| |
| 作者单位： | 南开大学,自动化系,天津,300071 |
| |
| 基金项目： | 国家自然科学基金;高等学校博士学科点专项科研项目;教育部新世纪支持计划 |
| |
| 摘 要： | 粒子群优化算法(PSO)是模拟生物群体智能的优化算法,具有良好的优化性能.但是群体收缩过快和群体多样性降低导致早熟收敛.本文引入了多样性指标和收敛因子模型来改进PSO算法,形成多样性收敛因子PSO算法(DCPSO),并且对现代资产投资的多目标规划问题进行了优化,简化了多目标规划的问题,并且表现出了比传统PSO算法更好性能.
|
| 关 键 词： | PSO算法(Particle Swarm Optimization) 现代资产投资 多样性 收敛因子模型 多目标优化 |
| 修稿时间： | 2006年5月9日 |
An Improved Particle Swarm Optimization and Its Application in Investment Operation |
| |
| LIU Yi,CHEN Zeng-qiang,YUAN Zhu-Zhi.An Improved Particle Swarm Optimization and Its Application in Investment Operation[J].Mathematics in Practice and Theory,2007,37(11):82-87. |
| |
| Authors: | LIU Yi CHEN Zeng-qiang YUAN Zhu-Zhi |
| |
| Abstract: | Particle swarm optimization(PSO) algorithm is a new population intelligence based algorithm and exhibits good performance on optimization.However the algorithm will fall into premature convergence due to the decrease of population diversity,caused by simplex information spread and fast convergence of population.In this paper,diversity control factor and convergence factor are introduced to improve the PSO,and become the DCPSO(diversity-guided convergent particle swarm optimization).By using the DCPSO,we can complete the multi-objective optimization based on modern investment.Experiments on benchmark functions shows DCPSO outperform standard PSO. |
| |
| Keywords: | PSO(Particle Swarm Optimization) modern investment diversity convergence factor multi-objective optimization |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
