一类改进的Vicsek模型的收敛性能

Convergence Efficiency of a Class of Improved Vicsek Model

摘要:针对描述群体动态行为的Vicsek模型收敛效率不高的问题,通过对群体网络拓扑关系的研究,提出一种使得群体中所有个体运动方向快速达到一致的新规则,该规则以个体邻域集合内运动方向偏差最大的两个邻居个体的运动方向的中值作为个体下一时刻的运动方向,取代Vicsek模型及其线性化模型的运动方向更新方程.在群体网络的初始位置分布满足拓扑连通的要求的前提下,基于NetLogo仿真平台,对比研究了新规则作用下的改进模型与Vicsek模型及其线性化模型的收敛效率.仿真结果表明,新规则控制下的改进模型达到方向一致的速度明显加快,可有效提高群体动态行为的收敛效率.

For the problem of the low convergence efficiency of Vicsek model,a new rule is proposed to parallel the motion directions of all individuals quickly based on the research of network topology relationships of the groups.Unlike the motion direction renewal equation of Vicsek model and its linear one,the rule forces an individual moving toward the middle of two neighbors＇ motion directions with the maximum deviation at next time.On the premise that initial position distribution of the group network is topology connectivity,a contrast study of the convergence efficiency of the improved model,Vicsek model and its linear model is done on NetLogo simulation platform.Simulation results show that the process of paralleling the directions is accelerated obviously and the convergence efficiency of dynamic swarming behavior is improved efficiently by the improved model under the control of the new rule.