Dynamic particle swarm optimization for solving high dimensional function

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (27): 36-37.

• 研究、探讨 • Previous Articles Next Articles

Dynamic particle swarm optimization for solving high dimensional function

SUN Lanlan1，WANG Xiaochao2

1.Zhejiang Industry Polytechnic College，Shaoxing，Zhejiang 321000，China
2.Luohe Medical College，Luohe，Henan 462002，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-09-21 Published:2011-09-21

求解高维函数优化的动态粒子群算法

孙兰兰1，王晓超2

1.浙江工业职业技术学院，浙江绍兴 321000
2.漯河医学高等专科学校，河南漯河 462002

Abstract

Abstract: To improve the search quality of the standard PSO algorithm for solving high-dimensional function，a dynamic particle swarm optimization algorithm is proposed.The strategy that particle trajectory is changed dynamically by adjusting the threshold value is used to make particles adaptability for the surrounding environment without the influence of evolutionary algebra，and the strong search capability of algorithm in iterative later is ensured.Simulations show that proposed algorithm has more powerful optimizing ability and higher optimizing precision in high-dimensional function optimization than literature algorithms.

Key words: particle swarm optimization algorithm, dynamic particle swarm optimization algorithm, high-dimensional function optimization

摘要： 针对基本粒子群优化算法对高维函数优化时搜索精度不高的缺陷，提出了一种动态粒子群优化算法。该算法采用了通过调节阈值对粒子运动轨迹进行动态改变的策略，使得粒子对周围环境的适应能力不受进化代数的影响，从而保证了算法在迭代后期仍具有较强的搜索能力。实验结果表明，与文献算法相比，该算法在处理高维函数优化时具有更强的寻优能力和更高的搜索精度。

关键词: 粒子群优化算法, 动态粒子群优化算法, 高维函数优化

SUN Lanlan1，WANG Xiaochao2. Dynamic particle swarm optimization for solving high dimensional function[J]. Computer Engineering and Applications, 2011, 47(27): 36-37.

孙兰兰1，王晓超2. 求解高维函数优化的动态粒子群算法[J]. 计算机工程与应用, 2011, 47(27): 36-37.

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Dynamic particle swarm optimization for solving high dimensional function

求解高维函数优化的动态粒子群算法

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