基于分层网格的铁路枢纽列流图编制优化仿真

Optimization and Simulation of Train Flow Diagram Compilation of Railway Terminal Based on Hierarchical Grid

铁路枢纽列流图是枢纽车流组织与列流组织的直观体现。目前铁路枢纽列流图大都依赖人工铺画,且现有的铁路枢纽列流图编制算法效率偏低。为实现铁路枢纽列流图编制优化与自动化,依据铁路枢纽列流图的图形元素正交化特征,采用列流线层次化和车站网格化方法,构建了以列流线和车站交叉点数目最小为主要优化目标的枢纽列流图编制分层网格模型。基于模型的非线性特征,设计自适应遗传算法进行求解,并通过引入修复算子缩小搜索空间来提高求解速度。最后将仿真绘制的列流图与现有算法及人工编制的列流图进行对比。结果表明,所提方法在区间间距和交叉点数目两个指标的表现均优于现有算法及人工铺画结果。

The train flow chart of a railway hub is an intuitive embodiment of the train flow organization and train flow organization of the hub.At present,most of the train flow maps of railway hubs rely on manual layout,and the ef-ficiency of the existing train flow graph compilation algorithms of railway hubs is low.In order to realize the optimiza-tion and automation of the compilation of train flow diagrams of railway hubs,based on the orthogonalization character-istics of graphic elements of train flow diagrams of railway hubs,train flow line hierarchization and station gridding methods are used to construct the number of train flow lines and station intersections.A hierarchical grid model for the pivot flow diagram was constructed with the main optimization objective of minimizing the number of train flow lines and station intersections.Then,based on the nonlinear characteristics of the model,an adaptive genetic algorithm was designed to solve the problem,and the search space was reduced by introducing a repair operator to increase the speed of the solution.Finally,the sequence flow diagram drawn by simulation was compared with the existing algorithm and the sequence flow diagram was prepared manually.The results show that the performance of the proposed method in the two indicators of interval spacing and the number of intersections is better than the existing algorithms and the results of manual paving.