空车动态优化配置的模型和方法研究

【作者】 梁栋；

【导师】 林柏梁；

【作者基本信息】 北京交通大学 ， 交通运输规划与管理， 2007， 博士

【摘要】 空车调配是铁路运输企业极为关注的一个问题。美国全国铁路空车车辆的走行公里约占总车辆走行公里的45%。我国铁路拥有运用货车近50余万辆,全路平均空车走行率约为30%左右,空车走行率最高的铁路局(公司)甚至可达60%左右。空车调配的好坏直接影响到车辆的利用效率、市场需求的满足程度以及运输组织的现代化水平。由于空车调配受到管理结构、网络能力、车流径路、计划任务、列车接续和货运需求等诸多因素的影响,因此,作为铁路部门公认的难题之一,空车调配问题在理论上和实践中都是一个值得深入研究的重要课题。由于我国铁路网络规模庞大,运输能力紧张和计划体制管理等特点,在国外研究已达三十载的动态空车调配问题,在我国却始终没有得到普遍关注。然而,空车调度随货运需求变化和车流接续波动的动态特性在铁路日常车辆运营中却是普遍存在的。而现行的空车调配计划的编制仍拘泥于传统的静态方法和历史经验,缺少动态优化的思想,因而不利于空车资源的有效配置和最大利用,也阻碍了生产效率的进一步提高和铁路市场化进程的加快。本论文在借鉴国内外研究成果的基础上,密切结合我国铁路运输组织管理特点,系统地提出了一系列具有实际应用价值的、能实现动态空车调配优化的模型和方法,从而为国内动态空车调配问题的深入研究奠定了理论基础。本论文的主要研究工作和创新点包括:1.首次提出了融合列车编组计划和列车运行图的服务时空网络概念,为研究动态空车调配问题提供了一种有效的技术手段和建模方法。在铁路局(公司)层面,创建了局(公司)管内的离散时段的空车服务时空网络和连续时间的空重车服务时空网络。离散时段的服务时空网络通过对时间轴的粗化分段,不仅成功缩减了网络规模而且增加了模型的弹性。而连续时间的服务时空网络借助细化到时间点的事件描述,成功实现了列车接续和列车车辆构成的精确优化。在整个路网层面,创建了全路网均衡运输下的OD时空网络。OD时空网络只考虑车辆在货流OD点的进出状态,而不涉及途中运输过程,它是对静态OD配流网络的一种动态处理,有利于空重车联合调整的优化建模。2.将铁路局(公司)日常的排空、配空和装车作业综合纳入优化,构建了两套基于完成日班计划要求的局(公司)管内动态空车调配模型,即空车调配的多阶段策略优更多还原

【Abstract】 Empty car distribution is a big issue that attracts more and more attention in the railway industry. In America, the percent of empty of total car kilometers is up to 45%. In our country, there are approximately 500,000 freight cars, and the average ratio of empty car kilometers to loaded car kilometers is about 30%, and the max ratio even perhaps 60%. Obviously, empty car distribution plays an important role in the efficiency of railcar utilization, the degree of meeting freight demand, and the modernization of railway operation. Because of the compositive influence of many factors, including management mode, network capacity, flow path, planned task, train connection and freight demand, as a common puzzle, empty car distribution tends to be so complex that it needs to be studied further in theory and practice.In recent 30 years, dynamic empty car distribution has been a popular topic in many developed countries. However, it hasn’t received more attention in our country because of the characteristics of large-scale railway network, limited transport capacity, and planned economy. In practice, the scheme of dispatching empty cars changes from time to time following the fluctuation of freight demand and train connection. So, the scheme, laid out by static planning method and historical experience, is unscientific and unhelpful for proper allocation and maximum utilization of empty car resources.Based on researches on the problem at home and abroad, this dissertation constructs a series of optimization models of dynamic empty car distribution, which are close to our railway operating features and have a great value in application.There are five main aspects, which are studied in detail in the dissertation presented as follows:1. This dissertation designs a service time-space network combined with train formation plan and train schedule for the first time, which makes for modeling dynamic empty car distribution. In the range of railway administration (or company), empty service time-space network with discrete period and empty-and-load service time-space network with continue time are both designed. Through dividing time axis into several period segments, the first one not only reduces the size of network successfully, but also increases the flexibility for modeling. It’s not the same that the second one describes each incident with detailed time, which realizes the exact optimization to train connection and train makeup. In the range of the whole railway network, OD time-space network with balanced transportation is created in order to optimize technical plan. The network has not relation to transportation of freight cars on the way, but refers to the situation of them in the origin and destination.2. This dissertation constructs two optimization models of dynamic empty car distribution for fulfilling daily and shift transport plan, which involve discharging empty cars, assigning empty cars and loading freights. One is the multi-stage optimization model of empty car distribution (MSMED), and the other is the model of optimizing empty and loaded car operation dynamically according to train schedule (MELOD). Because of MSMED neglecting the movement of loaded cars, it is approximate in forecast for empty car supply and evaluation of transport capacity. Moreover, some parameters in MSMED are so flexible that they can change with detailed situation of operation every day. Not only can MSMED make更多还原