物流网络中的冲突消除算法仿真

Simulation of Conflict Resolution Algorithm of Logistics Networks

传统的线性均衡算法不能充分考虑各要素之间的联系,造成冲突消除后物流网络的运输性能不高,为解决这一问题,提出基于神经网络的物流网络冲突消除算法。利用离散约束优化神经网络,采用前馈退火技术避免网络盲点,采用松紧机制加快收敛速度,最终在神经网络中进行迭代,实现物流网络中的冲突消除。实验表明,这种方法能够避免传统方法线性均衡算法的弊端,有效解决物流网络的冲突消除问题,提高物流网络的运输效率。

In this paper, we proposed an algorithm for conflict elimination in logistics networks on the basis of the neural network model, then introduced the working dynamics of the process and at the end, through an experiment, demonstrated that it could overcome the shortcoming of the traditional methods and effectively eliminate conflicts in the logistics networks.