粒子群算法中随机数参数的设置与试验分析-控制理论与应用.PDFVIP

27 11 Vol. 27 No. 11 2010 11 Control Theory Applications Nov. 2010 :2010 , (1. , 430081; 2. (), 300461; 3. , 400067) : , , . , , , , . , , , , , , , . : ; ; ; ; : TP39 : A Parameter setting and experimental analysis of the random number in particle swarm optimization algorithm LIU Zhi-xiong , LIANG Hua (1. College of Machinery and Automation, Wuhan University of Science and Technology, Wuhan Hubei 430081, China; 2. Postdoctoral Research Center, Tianjin Port (Group) Co LTD, Tianjin 300461, China; 3. School of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing 400067, China) Abstract: The parameters in particle swarm optimization have important effect on the optimization performance. The parameter setting of the random number in the particle swarm optimization model is analyzed by the experiments. First, because of different structures in different high-level languages, we find that in the program of particle swarm optimization algorithm, different components of a velocity vector may have different parameter settings for the corresponding random number in the particle velocity updating equation. Next, in continuous function optimization and benchmark tests of Job Shop scheduling, as well as the computation of the equipment-possession-quantity parameter optimization model, all results indicate that different parameter settings for the random number may cause significantly different effects on the optimization performance of particle swarm o