基于k最短路径的现代有轨电车线网优化

Optimization of modern tram network based on k-shortest path algorithm

为科学合理地进行现代有轨电车线网的优化与改进,基于现代有轨电车线网优化的约束条件,引入k最短路径算法进行线网优化.首先运用道路空间资源要素和线路重复系数这2个约束条件实现对初始网络图中有效边的筛选,形成备选线路集合,其次将非直线系数和节点综合重要度这2个约束条件组成联合熵权,将该联合熵权作为现代有轨电车最优路径的判定参数,从而构建满足多约束条件下的现代有轨电车线网优化方法.最后,以南京河西新城现代有轨电车线网优化为例,验证了该方法的有效性,表明k最短路径算法是适用于现代有轨电车线网规划的有效方法,该方法可为现代有轨电车线网规划提供参考.

In order to carry out the optimization and improvement of the modern tram network scientifically and rationally,the k-shortest path algorithm is introduced based on the constraint conditions of modern tram network optimization.Road space resource factors and path duplication factors are used to select the proper edges in the initial network and a set of alternative paths is formed.The non-linear coefficient and node comprehensive importance degree are combined into joint entropy weight,and the joint entropy weight is used as the judgment parameter of the optimal path of modern tram.Then,the modern optimization method for tram line is constructed.Finally,the effectiveness of the method is verified through the practical example of Nanjing Hexi new urban district modern tram network optimization.It is shown that the k-shortest path algorithm is an effective method for modern tram network planning.This method can provide a reference for urban tram network planning.