Optimization of intermodal rail operations and locomotive fleet management

优化多式​​联运铁路运营和机车车队管理

• 批准号: 513259-2017
• 负责人: RobertFrejinger, Emma
• 金额: $ 14.21万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=663451
• 关键词: Optimization; intermodal; rail; operations; locomotive

Canadian railway companies are both network and terminal operators and hence face many complex large-scale optimization problems. Many of these problems have been studied in the operations research (OR) literature for decades but the gap between the state-of-the-art and the state-of-practice is huge. In addition, both the scientific literature and the current industrial practice tend to treat decision problems in isolation of each other and most assume deterministic settings in which all input data are known with certainty. Uncertainty is particularly important as it affects planning and operations on a continuous basis. Decision support tools should thus not only take this uncertainty into account at the planning level but also provide ways to handle deviations from planned operations at the execution level. In this project we deal with two complementary families of problems currently faced in intermodal and freight rail transportation. The first family of problems concerns the planning and operation of intermodal rail transportation. We focus on a tactical network load block planning problem and three related issues: demand forecasting, load planning and track planning. The second family concerns the management of the locomotive fleet that is used to haul all types of cargo, including intermodal. The project addresses two specific problems: locomotive assignment and locomotive routing. ** Intermodal container freight transportation is the backbone of international trade, as well as of a large part of Canadian and North-American imports and exports. In this context, Canada benefits from having the largest rail network in the world to support its economic development. Rail is also the most environmentally friendly land freight transport mode. It is therefore not only beneficial to the Canadian railway industry but also to the Canadian society to make this mode of transport more efficient and cost effective. The results of this project can contribute to decreased delivery times, costs, and environmental footprint. Furthermore, developing decision aid tools that are based on mathematical models can help personnel in the railway industry make more informed decisions which, in turn, can lead to increased safety.************

加拿大铁路公司既是网络运营商又是终点站运营商，因此面临着许多复杂的大规模优化问题。这些问题中的许多已经在运筹学(OR)文献中研究了几十年，但最先进的技术和实践之间的差距是巨大的。此外，科学文献和当前的工业实践都倾向于相互孤立地处理决策问题，大多数都假定所有输入数据都是确定性的。不确定性尤其重要，因为它会持续影响规划和运作。因此，决策支持工具不仅应在规划一级考虑这一不确定性，而且还应在执行一级提供处理偏离计划业务的方法。在这个项目中，我们处理目前在多式联运和货运铁路运输中面临的两类互补问题。第一类问题涉及多式联运铁路运输的规划和运营。重点研究了一个战术网络负荷块规划问题以及与之相关的三个问题：需求预测、负荷规划和轨迹规划。第二个家族涉及用于运输所有类型货物(包括多式联运)的机车车队的管理。该项目解决了两个具体问题：机车分配和机车交路。**集装箱多式联运是国际贸易的支柱，也是加拿大和北美进出口的一大部分。在这方面，加拿大受益于拥有世界上最大的铁路网来支持其经济发展。铁路也是最环保的陆路货运方式。因此，提高这种运输方式的效率和成本效益不仅有利于加拿大铁路行业，也有利于加拿大社会。该项目的成果有助于减少交付时间、成本和环境足迹。此外，开发基于数学模型的决策辅助工具可以帮助铁路行业的人员做出更明智的决策，这反过来又可以提高安全性。