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Study on an improved quantum PSO algorithm for solving complex optimization problem

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成果类型:
期刊论文
作者:
Li, Mengxing;Wan, Zhuo*
通讯作者:
Wan, Zhuo
作者机构:
[Wan, Zhuo; Li, Mengxing] School of Communication and Electronic Engineering, Hunan City University, Yiyang, Hunan, 41300, China
语种:
英文
期刊:
International Journal of Hybrid Information Technology
ISSN:
1738-9968
年:
2016
卷:
9
期:
8
页码:
187-198
机构署名:
本校为第一机构
院系归属:
信息与电子工程学院
摘要:
Particle swarm optimization (PSO) algorithm is a population-based search algorithm by simulating the social behavior of birds within a flock. It is a simple and efficient optimization algorithm. But it exists the low computational speed and easy falling into local optimal solution in solving the complex problem. So the quantum theory, adaptive inertia weight, disturbance factor and diversity mutation strategy are introduced into the PSO algorithm in order to propose an improved PSO(IWDMDQPSO) algorithm in this paper. In the IWDMDQPSO algorithm, the quantum theory is used to change the updating...

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