| 改进的混合粒子群优化算法 |
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| 引用本文： | 高明正,金尚忠,张火明.改进的混合粒子群优化算法[J].中国计量学院学报,2008,19(3):260-264. |
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| 作者姓名： | 高明正 金尚忠 张火明 |
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| 作者单位： | 1. 中国计量学院,光学与电子科技学院,浙江,杭州,310018
2. 中国计量学院,计量测试工程学院,浙江,杭州,310018 |
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| 摘 要： | 针对粒子群算法后期收敛速度较慢,易陷入局部最优的缺点,提出了改进的混合粒子群算法.通过更改现有的速度更新公式,加入扰动项,以及引入交叉和变异算子等措施,改进了粒子群算法的性能.数值试验表明,改进后的粒子群算法在全局寻优和局部寻优能力上均得到提高,是一种有效的优化算法.
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| 关 键 词： | 粒子群算法 优化算法 交叉算子 变异算子 |
Improved hybrid particle swarm optimization algorithm |
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| GAO Ming-zheng,JIN Shang-zhong,ZHANG Huo-ming.Improved hybrid particle swarm optimization algorithm[J].Journal of China Jiliang University,2008,19(3):260-264. |
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| Authors: | GAO Ming-zheng JIN Shang-zhong ZHANG Huo-ming |
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| Affiliation: | GAO Ming-zheng, JIN Shang-zhong, ZHANG Huo-ming (1. College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China;2. College of Metrology and Measurement Engineering, China Jiliang University, Hangzhou 310018, China) |
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| Abstract: | The particle swarm optimization algorithm which has slow convergence rate and was easily trapping in local optimum was improved. By changing the velocity updating formula of PSO and by adding the disturbance term, crossover and mutation operator to the algorithm, the hybrid PSO＇s performance was significant improved. Experimental results indicate that the modified PSO algorithm is effective and has good ability on both global and local optimization problems. |
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| Keywords: | PSO optimization algorithm crossover operator mutation operator |
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