|
|||||
|
|
| 动态惯性权重粒子群优化算法 | |
| 引用本文： | 虞斌能,连志刚,焦斌. 动态惯性权重粒子群优化算法[J]. 上海电机学院学报, 2008, 11(3) |
| 作者姓名： | 虞斌能 连志刚 焦斌 |
| 作者单位： | 1. 上海电机学院电气学院,上海,200240;华东理工大学,信息科学和工程学院,上海,200237 2. 上海电机学院经济管理学院,上海,200245 3. 上海电机学院电气学院,上海,200240 |
| 摘 要： | 针对基本粒子群优化(Particle Swarm Optimization,PSO)算法的不足,提出动态惯性权重粒子群优化算法,其惯性系数随算法进化而动态减少。仿真结果验证了该改进算法的有效性:算法的收敛速度比基本PSO算法的收敛速度快;同时,算法得到的最优解比基本PSO算法好。 |
| 关 键 词： | 粒子群优化 惯性权重 进化计算 |
Particle Swarm Optimization Algorithm with a Dynamic Inertia Weight |
|
| YU Binneng,LIAN Zhigang,JIAO Bin. Particle Swarm Optimization Algorithm with a Dynamic Inertia Weight[J]. JOurnal of Shanghai Dianji University, 2008, 11(3) | |
| Authors: | YU Binneng LIAN Zhigang JIAO Bin |
| Affiliation: | YU Binneng(1a; 2); LIAN Zhigang(1b); JIAO Bin(1a)(1.a.School of Electric; Shangahi 200240; b.School of Economics Management; Shanghai 200245; Shanghai Dianji University; China; 2.School of Information Science and Engineering; East China University of Science and Technoloty; Shanghai 200237; China); |
| Abstract: | An improved particle swarm optimization algorithm(IPSO) is proposed to improve the performance of standard PSO.The dynamic inertia weight is introduced in IPSO and its value decreases with iterative generation increasing.The algorithm is validated with a set of 6 benchmark functions and compared with standard PSO.Experiment results indicate that the IPSO improves the optimization performance on the benchmark functions significantly. |
| Keywords: | particle swarm optimization（PSO） inertia weight parameter |
| 本文献已被 维普 万方数据 等数据库收录！ | |