| 基于差分及模拟退火的混合粒子群算法 |
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| 引用本文： | 褚国娟,马春丽,宁必锋.基于差分及模拟退火的混合粒子群算法[J].计算机与现代化,2010(5):19-20,23. |
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| 作者姓名： | 褚国娟 马春丽 宁必锋 |
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| 作者单位： | 渤海大学数学系,辽宁,锦州,121013 |
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| 摘 要： | 粒群算法是一种新型的群体进化计算方法，已经在一些工程领域得到了广泛的应用，本文鉴于该算法存在收敛速度较慢，易陷入局部极值的缺点，提出一种基于差分及模拟退火的混合粒子群算法。通过对三种进化算法各自优势的分析与结合，得到一种改进的粒子群算法。
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| 关 键 词： | 粒子群 差分算法 模拟退火 优化 |
Hybrid Particle Swarm Optimization Algorithm Based on Differential and Simulated Annealing |
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| CHU Guo-juan,MA Chun-li,NING Bi-feng.Hybrid Particle Swarm Optimization Algorithm Based on Differential and Simulated Annealing[J].Computer and Modernization,2010(5):19-20,23. |
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| Authors: | CHU Guo-juan MA Chun-li NING Bi-feng |
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| Affiliation: | Department of Mathematics/a>;Bohai University/a>;Jinzhou 121013/a>;China |
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| Abstract: | Particle swarm optimization is a new evolutionary computation method of the group and is widely used in a few projects.Because the convergence speed is slow and easy to fall into local minimum,the paper proposes a hybrid particle swarm optimization algorithm based on differential and simulated annealing.Through analysis and combining of their respective advantages of the three kinds of evolutionary algorithm,an improved particle swarm optimization is obtained. |
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| Keywords: | particle swarm difference algorithm simulated annealing optimization |
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