基于增强拉格朗日乘子法的容量制约交通分配问题研究(英文)

传统的交通分配问题(TAP)没有容量的限制,但是事实上,路段和网络都有其自身的容量限制。传统的用户均衡网络模型允许分配的交通流量结果超过其容量,这显然是不合理的。首先,介绍了起点算法的基本原理及其有效的实现,并运用一个算例网络进行交通分配;然后,运用增强拉格朗日乘子法针对具有容量限制的该网络重新进行交通分配,并将两种结果进行比较。实验结果表明:增强拉格朗日乘子法具有良好的运算性能和效率,并且更具有实际意义,能够更加合理的运用到实际的交通分配问题中。

Study on Capacity-Constrained Traffic Assignment Based on Augmented Lagrange Multiplier

The traffic assignment problem(TAP) is traditionally defined without side constraints.In fact,link and network have their intrinsic capacity.The traditional user equilibrium model allows more traffic flow than capacity,which is clearly unreasonable.Firstly,the origin-based algorithm including its theory and efficient implementation was introduced.And the traffic assignment was made with a network example.Then the augmented Lagrange multiplier method was used to made traffic assignment of the network with the link capacity constraints.The results of the two methods were compared with each other.The augmented Lagrange multiplier method has good convergence performance and efficiency.The comparison results show that the latter has more practical significant,which can be better applied in actual traffic assignment problem.