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作 者:方波 魏玉光[1] 杨浩[1] FANG Bo;WEI Yuguang;YANG Hao(School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China)
出 处:《铁道学报》2021年第10期12-19,共8页Journal of the China Railway Society
基 金:中国铁路总公司科技研究开发计划(P2018X011)。
摘 要:基于多商品流服务网络设计原理,在构建列车备选集的基础上,将编组计划问题转化为备选列车服务网络上的车流分配问题,并建立基于列车备选集的单组列车编组计划两阶段线性规划模型,实现车流径路和编组计划的分阶段优化。第一阶段(车流径路模型)基于K-短路算法和绕道率求解各OD对的最优车流径路;第二阶段(编组计划模型)以最优车流径路生成的列车备选集为输入,引入列车开行决策变量和车流分配决策变量,综合考虑车站改编能力、分类线数量和流平衡等约束,求解最优列车服务和车流分配方案。分别以小规模和大规模路网案例对模型进行求解验证,结果表明,两阶段线性规划模型能够快速准确地得到最优单组列车编组计划,可有效降低编组计划的总消耗,求解质量优于非线性模型,为求解大规模路网单组列车编组计划提供了新方法。Based on the design principle of multi-commodity flow service network, this paper transformed the train formation plan(TFP) problem into the traffic distribution problem on candidate train service networks on the basis of constructing the candidate train set, and established a two-stage linear programming model of single-block TFP based on the candidate train set to realize the phased optimization of traffic routing and TFP. The optimal traffic path of each OD pair was solved by the first stage of the model(traffic routing model) based on K-shortest path algorithm and detour ratio. The candidate train set generated by the optimal traffic path was taken as input in the second stage(TFP model). The train operation decision variables and traffic distribution decision variables were introduced to solve the optimal train services and traffic assignment plan considering constraints such as yard classification capacity, number of classification tracks and flow balance. The case study shows that the two-stage linear programming model can obtain the optimal solution quickly and accurately, effectively reduce the total consumption of TFP, and deliver better solution quality than that of the nonlinear model, which provides a new method for solving the single-block TFP of large-scale rail networks.
分 类 号:U292.3[交通运输工程—交通运输规划与管理]
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