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《Journal of University of Electronic Science and Technology of China》 2005-05
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Particle Swarm Optimization Algorithm and Comparison with Genetic Algorithm

SHEN Yan1,GUO Bing2,GU Tian-xiang1 (1. School of Electromechanical Engineering, UEST of China Chengdu 610054; 2. School of Computer, Sichuan Univarcity Chengdu 610041)  
Particle swarm optimization, rooting from simulation of swarm of bird, solves optimization problem. Firstly, discusses particle swarm optimization algorithm principle and step of implementation, and then analyzes each of parameter. Particle swarm optimization algorithm compares with genetic algorithm through the same mathematic function. The comparative result indicates that Particle swarm optimization algorithm can obtain the optimum solutions more easily than genetic algorithm and it is a good optimization method with strong competition.
【CateGory Index】: O242.23;
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