[1]刘宏达,马忠丽.均匀粒子群算法[J].智能系统学报,2010,5(4):336-341.
LIU Hong-da,MA Zhong-li.A particle swarm optimization algorithm based on uniform design[J].CAAI Transactions on Intelligent Systems,2010,5(4):336-341.
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LIU Hong-da,MA Zhong-li.A particle swarm optimization algorithm based on uniform design[J].CAAI Transactions on Intelligent Systems,2010,5(4):336-341.
均匀粒子群算法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
5
期数:
2010年第4期
页码:
336-341
栏目:
学术论文—人工智能基础
出版日期:
2010-08-25
- Title:
- A particle swarm optimization algorithm based on uniform design
- 文章编号:
- 1673-4785(2010)04-0336-06
- Keywords:
- PSO; uniform design; realtime optimization; key population
- 分类号:
- TP18
- 文献标志码:
- A
- 摘要:
- 由于粒子群算法(PSO)本质上的随机性，其搜索质量和速度也呈随机性.这使得普通的粒子群算法难以满足某些需要快速优化的工程需要.利用均匀设计方法产生PSO算法的初始种群（或关键代次种群），可以使种群中的粒子在搜索空间分布更均匀，更好地保持分散性.算法中给出了4种种群的生成方案，通过测试和对比分析表明:基于值域分割的均匀设计种群生成法能使算法的搜索效果最好；算法可以在不丧失搜索精度和效率的前提下，提高搜索效率和搜索精度的稳定性，有效减少粒子聚集和早熟的发生.
- Abstract:
- In a normal PSO algorithm, particle populations are usually produced randomly, leading to variations in search quality and speed. Such algorithms cannot be used to solve engineering problems that must be optimized quickly. In order to solve such problems, a PSO algorithm based on uniform design was used to generate initial PSO populations. This made the distribution of particles more uniform in the search space. Four methods for generation of particle swarms were studied. Test results showed that search precision was considerably improved if the generation of a particle swarm by the uniform design method was based on value range division. That method maintained search efficiency and precision, stabilized search efficiency and precision, and reduced the possibility of swarm aggregation and premature convergence.
- 参考文献/References:
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备注/Memo
收稿日期：2009-09-05.
基金项目：中央高校基本科研业务专项资金资助项目(HEUCFT1005).
通信作者：刘宏达.E-mail:liuhd405@163.com.
作者简介：
刘宏达，男，1976年生，副教授，主要研究方向为群智能理论及其应用，发表学术论文12篇.
马忠丽，女，1974年生，副教授，主要研究方向为机器视觉检测技术
更新日期/Last Update:
2010-09-20