DocumentCode :
477463
Title :
One Improved Discrete Particle Swarm Optimization Based on Quantum Evolution Concept
Author :
Li Xuyuan ; Xu, Hualong ; Cheng, Zhaogang
Author_Institution :
Xi´´an Res. Inst of Hi-Tech, Xian
Volume :
1
fYear :
2008
fDate :
20-22 Oct. 2008
Firstpage :
96
Lastpage :
100
Abstract :
In order to solve the combinatorial optimization problem effectively, one improved discrete particle swarm optimization based on quantum evolution concept is proposed in the paper. Firstly, The quantum angle is defined and it is restricted in the range from -pi/2 to 0. Secondly, a new velocity update is proposed, it can update adaptively and can avoid the local optima. Thirdly, under the thought of quantum evolution, the particle can be transferred from decimal code to binary code, so the algorithm can be used to solve the discrete problem. From the experiment, we can learn that the algorithm can realize global optima effectively.
Keywords :
binary codes; combinatorial mathematics; particle swarm optimisation; quantum computing; binary code; combinatorial optimization; decimal code; discrete particle swarm optimization; global optima; quantum angle; quantum evolution concept; velocity update; Acceleration; Automation; Binary codes; Birds; Cities and towns; Convergence; Educational institutions; Marine animals; Particle swarm optimization; Quantum computing; discrete; particle swarm optimization; quantum;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
Type :
conf
DOI :
10.1109/ICICTA.2008.371
Filename :
4659450
Link To Document :
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