标题： 基于实践的优化方法在战略机车分配问题中的应用 显示英文标题

标题： Practice-Based Optimization for the Strategic Locomotive Assignment Problem

摘要： 本研究解决了在大型货运铁路网络中高效分配机车的挑战，其中运营复杂性和功率不平衡使得成本效益规划变得困难。 它提出了一种用于机车分配问题（LAP）的战略优化框架，该框架与一家主要的北美一级货运铁路公司合作开发。 该问题被建模为基于网络的整数规划，在循环时空网络上生成可重复的每周机车分配计划。 该模型涵盖了全面的实际运营约束，并联合优化了取车和送车机车作业事件的布置，提高了下游规划的有效性。 为了首次精确求解大规模实例，引入了新颖的约简规则，大幅减少了时空网络中的轻载行驶弧数量。 大量的计算实验展示了在各种实际约束条件下真实实例的性能和权衡。 除了提供可扩展的高质量解决方案外，所提出的框架作为一种基于现代货运铁路运营现实的实用决策支持工具。 显示英文摘要

摘要： This study addresses the challenge of efficiently assigning locomotives in large freight rail networks, where operational complexity and power imbalances make cost-effective planning difficult. It presents a strategic optimization framework for the Locomotive Assignment Problem (LAP), developed in collaboration with a major North American Class I Freight Railroad. The problem is formulated as a network-based integer program over a cyclic space-time network, producing a repeatable weekly locomotive assignment plan. The model captures a comprehensive set of real-world operational constraints and jointly optimizes the placement of pick-up and set-out locomotive work events, improving the effectiveness of downstream planning. To solve large-scale instances exactly for the first time, novel reduction rules are introduced to dramatically reduce the number of light travel arcs in the space-time network. Extensive computational experiments demonstrate the performance and trade-offs on real instances under a variety of practical constraints. Beyond delivering scalable, high-quality solutions, the proposed framework serves as a practical decision-support tool grounded in the operational realities of modern freight railroads.