Particle swarm optimization algorithm based on markov model and its stochastic process analysis

doi:10.3778/j.issn.1002-8331.2009.31.016

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (31): 49-52.DOI: 10.3778/j.issn.1002-8331.2009.31.016

• 研究、探讨 • Previous Articles Next Articles

Particle swarm optimization algorithm based on markov model and its stochastic process analysis

YUAN Dai-lin^1，2，CHEN Qiu¹

1.School of Mechanics and Engineering，Southwest Jiaotong University，Chengdu 610031，China
2.School of Mathematics，Southwest Jiaotong University，Chengdu 610031，China

Received:2009-05-07 Revised:2009-06-23 Online:2009-11-01 Published:2009-11-01
Contact: YUAN Dai-lin

马氏模型PSO及其随机过程分析

袁代林^1，2，陈虬¹

1.西南交通大学力学与工程学院，成都 610031
2.西南交通大学数学学院，成都 610031

通讯作者: 袁代林

Abstract

Abstract: Inspired by the theoretic analysis of genetic algorithm based on markov process，a new form of particle swarm optimization algorithm is advanced，which is convenient for analysis by the theory of markov process.The particle of new algorithm only memorizes the information of swarm in finite steps，and forgets the old information.Then the markov process model is established.The simulations of functions optimization show that the new algorithm has good ability to find the global solution，and the homogeneous markov process is got from the new algorithm.

Key words: particle swarm optimization, markov process, function optimization

摘要： 受遗传算法马氏模型理论分析的启发，提出了一种便于用马氏过程理论分析的微粒群算法。该算法中的个体仅记忆群体在进化过程中有限步内的信息，忘掉以前的信息，以建立算法的马氏过程数学模型。通过函数优化的数值模拟验证了新算法具备优良的寻优能力，同时论证了新算法是齐次马氏过程。

关键词: 微粒群算法, 马氏过程, 函数优化

CLC Number:

TP301

YUAN Dai-lin^1，2，CHEN Qiu¹. Particle swarm optimization algorithm based on markov model and its stochastic process analysis[J]. Computer Engineering and Applications, 2009, 45(31): 49-52.

袁代林^1，2，陈虬¹. 马氏模型PSO及其随机过程分析[J]. 计算机工程与应用, 2009, 45(31): 49-52.

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Particle swarm optimization algorithm based on markov model and its stochastic process analysis

马氏模型PSO及其随机过程分析

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