既有铁路线路改建设计优化模型与方法

Optimization model and method for existing railway alignment reconstruction

随着铁路客货运量需求大幅度增长,为增强铁路网的运输能力,除了新建铁路之外,大量等级较低的既有铁路急需进行改建。目前,既有铁路线路改建设计依赖于人工经验,因此急需对既有铁路线路智能化改建设计开展研究,以提高改建的质量与效率。但是,现有的线路优化研究大多集中于新建铁路线路,几乎没有考虑既有线路与改建线路之间的复杂耦合关系,而导致这些方法无法直接运用于既有铁路线路改建优化设计中。针对铁路线路改建设计优化模型与方法,首先需要构建既有铁路线路改建优化模型。在该优化模型中,以逐层检测智能化分段结果中的线形几何参数作为设计变量,以改建综合工程费用为目标函数,并考虑几何、结构物和禁区3种复杂约束。为求解上述模型,提出“两阶段”改建优化方法。在第1阶段中,构建一种逐层筛选自动分段机制,根据改建线路设计标准、工程师设计需求等限制因素,将既有铁路线路划分为若干个利用段和改建段。在第2阶段中,基于广义距离变换算法,考虑改建段与相邻利用段之间的复杂耦合关系,提出一种“多向扫描”策略,运用于搜索研究区域内最优的改建线路。将上述优化模型与方法运用于一个复杂的实际铁路案例,最终机选方案要比最优人工方案节省7.2%的改建综合工程费用。通过详细结果分析验证了本文方法的有效性。

With the substantial growth of railway traffic demand,to enhance the transport capacity of the railway network,in addition to new railways,numerous low-grade existing railways need to be reconstructed.At present,the reconstruction of existing railways largely depends on manual design.Thus,to improve the quality and efficiency of reconstruction design,it is urgent to study the intelligent reconstruction of existing railway alignments.However,most of the existing researches on alignment optimization focus on new railway alignments,without considering the complex coupling relations between existing and reconstructed alignments.Thus,these methods cannot be directly applied to the optimization design of existing railway alignment reconstruction.For the optimization model and method for existing railway alignment reconstruction,an optimization model was developed by defining the geometric parameters of the automatic segmentation results as design variables.The reconstruction cost was formulated as an objective function,and three categories of constraints(geometric,structural and location constraints)were considered.To solve this model,a two-stage method was developed.Firstly,an automatic segmentation mechanism for sequential screening was proposed for segmenting existing alignments into reused and reconstructed sections.Then,a multi-directional scanning strategy was devised and incorporated into distance transform to search for redesigned alignments.By being applied to a real-world case,the optimized solution can save 7.2%of the reconstruction cost compared with the best manual solution.The effectiveness of the proposed method is verified through data analysis.