Particle Swarm Optimization Based on Clustering in Searching Process
The population distribution of Particle Swarm Optimization (PSO) directly concerns global convergence and searching efficiency of PSO. The reasonable setting of population distribution and operational parameters is an important problems in the application of PSO to perform optimization calculation. Based on the study on how to set the population distribution, such conclusion can be drawn that the population distribution must reflect the information on solution space scientifically. The PSO based on the population distribution of clustering is proposed. The population distribution was analyzed according to the discrepancy in the solution space and objective function space. The integrated clustering index, which combines the fitness value and space location, was applied to design the population distribution. Simulation results show that the method is feasible and effective.
particle swarm optimization the population distribution clustering fitness value normalization
Dakuo He Yi Meng Erwei Zhang Guanyu Wang
School of Information Science and Engineering Northeastern University Shenyang, China
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
2896-2899
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）