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| 混合型粒子群优化算法研究 | |
| 引用本文： | 章慧云,黄晓伟,张红华,徐杰. 混合型粒子群优化算法研究[J]. 计算机应用研究, 2011, 28(5): 1631-1633. DOI: 10.3969/j.issn.1001-3695.2011.05.009 |
| 作者姓名： | 章慧云 黄晓伟 张红华 徐杰 |
| 作者单位： | 1. 江西省水利水电学校,南昌,330013;华东交通大学,南昌,330013 2. 江西省水利工程技师学院,南昌,330013 3. 江西省水利水电学校,南昌,330013 4. 江西交通职业技术学院,南昌,330013 |
| 摘 要： | 为了改进粒子群算法的性能，提出了融合其他算法优点的混合型粒子群算法。对三种主流的混合粒子群优化算法(基因粒子群、免疫粒子群、混沌粒子群)分别从混合目的、混合方式、实现步骤、算法优化性能等多个方面进行了研究，给出了这三种混合粒子群算法的优缺点及适用范围。 |
| 关 键 词： | 混合型粒子群算法；算法分析；基因粒子群算法；免疫粒子群算法；混沌粒子群算法 |
| 收稿时间： | 2010-11-01 |
| 修稿时间： | 2010-12-05 |
Study on hybrid particle swarm optimization algorithms |
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| ZHANG Hui-yun,HUANG Xiao-wei,ZHANG Hong-hu,XU Jie. Study on hybrid particle swarm optimization algorithms[J]. Application Research of Computers, 2011, 28(5): 1631-1633. DOI: 10.3969/j.issn.1001-3695.2011.05.009 | |
| Authors: | ZHANG Hui-yun HUANG Xiao-wei ZHANG Hong-hu XU Jie |
| Affiliation: | ZHANG Hui-yun1,2,HUANG Xiao-wei3,ZHANG Hong-hua1,XU Jie4(1.Jiangxi School of Water Resources & Electric Power,Nanchang 330013,China,2.East China Jiaotong University,3.Jiangxi Institute of Hydraulic Engineering Technician,4.Jiangxi Vocational & Technical College,China) |
| Abstract: | In order to improve the performance of particle swarm optimization algorithm(PSO), hybrid particle swarm algorithm which integrating the advantages of other algorithms was proposed. The three major hybrid particle swarm optimization (Gene PSO , immune PSO, chaotic PSO) were studied on mixed purpose, mixing methods, implementation steps, algorithm optimization performance and other aspects , and the advantage and disadvantage of every hybrid particle swarm optimization and its application scope were given. |
| Keywords: | hybrid particle swarm algorithm algorithm analysis gene PSO immune PSO chaotic PSO |
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