The Improved Cooperated Particle Swarm Optimization Algorithm with Dynamic Information Adjustment and Controlled Speed
Fu Li-hui1,2,YIN Wen-qing1
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1 College of Engineering,Nanjing Agricultural University,Nanjing 210031,China2 Faculty of Electronic and Electrical Engineering,Huaiyin Institute of Technology, Jiangsu Huaian, 223003,China
In view of the premature convergence of PSO which often caused by the loss of diversity,a improved cooperated particle swarm optimization algorithm with dynamic information adjustment and controlled speed is proposed.On the basis of optimum value of particles and global optimization,it add the optimum value in groups to control the flight states of particles by divided subgroups,and using the current optimization number to dynamically adjust the contribution rate of each best value for determination the next state of particle,fusing effectively three reference information which seek the better ability of optimization.Research and realize the possibility and feasibility of convergence speed control by adjusting of the number of group,the algorithm have more appropriate convergence rate while guaranteeing the convergence precision.Finally,the theory analysis results is inspected by simulation experiments and show that the new algorithm has better convergence accuracy and controlled speed compared to other PSO algorithms.
Fu Li-hui;YIN Wen-qing.
The Improved Cooperated Particle Swarm Optimization Algorithm with Dynamic Information Adjustment and Controlled Speed [J]. Journal of Vibration and Shock, 2012, 31(21): 120-125
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