| 粒子群优化算法惯量权重控制方法的研究 |
| |
| 引用本文： | 刘杨,田学锋,詹志辉. 粒子群优化算法惯量权重控制方法的研究[J]. 南京大学学报(自然科学版), 2011, 0(4): 364-371 |
| |
| 作者姓名： | 刘杨 田学锋 詹志辉 |
| |
| 作者单位： | 中山大学计算机科学系;中兴通讯股份有限公司; |
| |
| 摘 要： | 粒子群优化算法（PSO）是一类随机全局优化技术,算法简单、容易实现而功能强大,目前已成为国际进化计算界研究的热点.粒子群算法的性能受到参数惯量权重ω的影响,大量研究表明,较小的ω具有较好的局部搜索能力,可提高求解精度;较大的ω具有较好的全局搜索能力,在一定程度上可以避免陷入局部最优.很多研究者提出了多种动态调整惯量权重...
|
| 关 键 词： | 粒子群优化算法 惯量权重 线性递减法 随机法 非线性递减法 |
Research on inertia weight control approaches in particle swarm optimization |
| |
| Liu Yang,Tian Xue-Feng,Zhan Zhi-Hui. Research on inertia weight control approaches in particle swarm optimization[J]. Journal of Nanjing University: Nat Sci Ed, 2011, 0(4): 364-371 |
| |
| Authors: | Liu Yang Tian Xue-Feng Zhan Zhi-Hui |
| |
| Affiliation: | Liu Yang1,Tian Xue-Feng2,Zhan Zhi-Hui1 (1.Department of Computer Science,Sun Yat-sen University,Guangzhou,510275,China,2.Zhongxing Telecom Equipment Corporation,Shenzhen,Guangdong,518057,China) |
| |
| Abstract: | Particle swarm optimization(PSO) is a kind of global optimization technique which is simple,easy for implementation,and powerful.As the inertia weight parameter affects the algorithm performance significantly,this paper makes a systematic introduction and comparisons on the current typical inertial weight control approaches,including linearly decreasing approach,random approach,concave decreasing approach,and convex decreasing approach.The research is based on 10 different unimodal and multimodal benchmark ... |
| |
| Keywords: | particle swarm optimization inertia weight linearly decreasing random non-linearly decreasing |
| 本文献已被 CNKI 等数据库收录！ |
|
