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《Computer Engineering and Applications》 2003-13
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A Novel Particle Swarm Optimization Algorithm

Wang Suihua 1 Feng Naiqin 1 Li Aiguo 21 (Department of Computer Science,Henan Normal University,Xinxiang,Henan453002) 2 (Department of Computer Science,Xi'an University of Science and Technology,Xi'an710054)  
Particle swarm optimization(PSO)is an efficient stochastic global optimization technique making use of a particle population,where each particle represents a solution to the problem being optimized.The particle swarm algorithms find optimal regions of complex search spaces through the interaction of individuals in a population of particles.A novel variant of original PSO algorithm is proposed in this paper.An item of integral control and a constraint of position are added to the traditional position update rule in order to improve performance of original PSO algorithm.The experiment results demonstrate that proposed algorithm is superior to original PSO algorithm and modified PSO algorithm with inertia weight reduced linearly.
【CateGory Index】: TP18
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