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| 基于锦标赛选择遗传算法的随机微粒群算法 | |
| 引用本文： | 夏桂梅,曾建潮. 基于锦标赛选择遗传算法的随机微粒群算法[J]. 计算机工程与应用, 2007, 43(4): 51-53,84 |
| 作者姓名： | 夏桂梅 曾建潮 |
| 作者单位： | 太原科技大学,系统仿真与计算机应用研究所,太原,030024;太原科技大学,系统仿真与计算机应用研究所,太原,030024 |
| 基金项目： | 教育部科学技术研究项目 |
| 摘 要： | 以保证全局收敛的随机微粒群算法SPSO为基础。提出了一种改进的随机微粒群算法-GAT-SPSO。该方法是在SPSO的进化过程中．以锦标赛选择机制下的遗传算法所产生的最优个体来代替SPSO中停止的微粒，参与下一代的群体进化。通过时三个多峰的测试函数进行仿真，其结果表明：在搜索空间维数相同的情况下，GAT-SPSO的收敛率厦收敛速度均大大优于SPSO。 |
| 关 键 词： | 随机微粒群算法 遗传算法 锦标赛选择 全局优化 |
| 文章编号： | 1002-8331（2007）04-0051-03 |
| 修稿时间： | 2006-05-01 |
Stochastic particle swarm optimization algorithm based on genetic algorithm of tournament selection |
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| XIA Gui-mei,ZENG Jian-chao. Stochastic particle swarm optimization algorithm based on genetic algorithm of tournament selection[J]. Computer Engineering and Applications, 2007, 43(4): 51-53,84 | |
| Authors: | XIA Gui-mei ZENG Jian-chao |
| Affiliation: | Division of System Simulation and Computer Application,Tianyuan University of Science and Technology,Taiyuan 030024,China |
| Abstract: | Based on the stochastic particle swarm optimization algorithm that guarantees global convergence,an improved stochastic particle swarm optimization algorithm-GAT-SPSO is proposed.During the evolution of SPSO,the best particle produced by genetic algorithm of tournament selection substitutes for the stopping particle and takes part in the evolution of next generation.Through the experiments of three multi-modal test functions,the result of simulation proves that the speed of convergence and the rate of convergence for GAT-SPSO are better than SPSO at the same dimension of search space. |
| Keywords: | Stochastic Particle Swarm Optimization(SPSO) Genetic Algorithm(GA) tournament selection global optimization |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |