基于拉格朗日神经网络的容量网络流量分配

Hasan DALMAN
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摘要

在本研究中,我们利用神经网络方法来获得具有容量限制的网络流量分配问题的用户平衡。首先将网络流量分配的优化问题转化为拉格朗日问题。通过考虑梯度法,得到了一个微分方程组。然后,用龙格-库塔法求解微分方程组。通过数值算例验证了所提神经网络方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Capacitated Network Traffic Assignment using Lagrange Neural Networks
In this study, we utilize a neural network methodology to obtain user equilibrium for network traffic assignment problems with capacity constraints. The optimization problem associated with network traffic assignment is first transformed into a Lagrange problem. By considering the gradient method, a system of differential equations is obtained. Subsequently, the system of differential equations is solved using the Runge-Kutta method. The effectiveness of the proposed neural network approach is demonstrated through a numerical example.
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