| 多元最优信息分组延迟粒子群算法 |
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| 引用本文： | 刘建华. 多元最优信息分组延迟粒子群算法[J]. 现代电子技术, 2007, 30(4): 83-85 |
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| 作者姓名： | 刘建华 |
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| 作者单位： | 福建师范大学,数学与计算机科学学院,福建,福州,350007 |
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| 摘 要： | 在简要介绍基本PSO算法的基础上,提出多元最优信息分组算法:选择m个最优信息,分成m个组,每个微粒属于离自己最近的最优微粒所处的小组。当经过一定的运行延迟周期后,合并小组,直到只剩下最后一个小组。同时,对新算法进行描述并以典型优化问题的实例仿真验证了MGPSO算法的有效性。
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| 关 键 词： | 粒子群算法(PSO算法) 多元最优信息 分组延迟 收敛性 |
| 文章编号： | 1004-373X（2007）04-083-03 |
| 收稿时间： | 2006-06-28 |
| 修稿时间： | 2006-06-28 |
Multi-Optimum Grouping and Delaying Partical Swarm Optimization |
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| LIU Jianhua. Multi-Optimum Grouping and Delaying Partical Swarm Optimization[J]. Modern Electronic Technique, 2007, 30(4): 83-85 |
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| Authors: | LIU Jianhua |
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| Affiliation: | School of Mathematics and Computer Seienee,Fujian Normal University,Fuzhou,350007,China |
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| Abstract: | Particle Swarm Optimization(PSO) is a new population-based evolution algorithm and exhibits good performance on optimization.However,during the evolution of algorithm,exploration and convergence of PSO is a contradiction.In this paper,a new PSO algorithm,called as MGPSO,is proposed in which m optimum are chosed to be grouped as m group,each partical belong to the group which the distance between it and the optimum is minimal.After runing contant times,the optimum becomes half until the number of optimum is only one.The simulation results on benchmark functions show the efectiveness of the new algorithm. |
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| Keywords: | PSO multi-optimum grouping and delaying convergence |
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