Integrating rolling stock scheduling with train unit shunting

Abstract

Highlights• We develop two integrated frameworks for scheduling rolling stock and train unit shunting.• We provide a comparison of several methods for solving the Track Allocation Problem.• We give a counter example demonstrating the suboptimality of a previously proposed optimal method. AbstractIn this paper we consider integrating two important railway optimization problems, in particular the Rolling Stock Scheduling Problem and the Train Unit Shunting Problem. We present two similar branch-and-cut based approaches to solve this integrated problem and, in addition, provide a comparison of different approaches to solve the so-called Track Assignment problem, a subcomponent of the Train Unit Shunting problem. In this analysis we demonstrate, by way of a counter example, the heuristic nature of a previously argued optimal approach. For the integrated problem we analyze the performance of the proposed approaches on several real-life case studies provided by DSB S-tog, a suburban train operator in the greater Copenhagen area. Computational results confirm the necessity of the integrated approach; high quality solutions to the integrated problem are obtained on instances where a conventional, sequential approach ends in infeasibility. Furthermore, for the considered instances, solutions are typically found within a few minutes, indicating the applicability of the methodology to short-term planning.

Resolution of coupling order and station level constraints in train unit scheduling

“…Lei et al (2017) analyze the potential station shunting issues caused by a solution at the network level without the determination of coupling orders. In addition, a branch-and-cut algorithm of connecting flow level and depot shunting is proposed by (Haahr and Lusby 2017) with the simplified assumption that tracks are all dead-end. For the train unit scheduling problem, the network level assigns train unit types and quantities to each timetabled trip.…”

Solving Unsplittable Network Flow Problems with Decision Diagrams

“…Many variants of train routing and scheduling problems with different objective functions and set of constraints under deterministic and stochastic conditions have been introduced and vastly studied in the literature; see surveys by Cordeau, Toth, and Vigo (1998), Harrod and Gorman (2010), Lusby et al (2011), Cacchiani andToth (2012), andTurner et al (2016) for different problems classifications and structures. Mixed integer linear and nonlinear programming formulations are among the most frequent exact approaches to model different classes of these problems (Jovanović and Harker 1991, Huntley et al 1995, Sherali and Suharko 1998, Lawley et al 2008, Haahr and Lusby 2017, Davarnia et al 2019. Proposed solution techniques include but are not limited to branch-and-bound methods (Jovanović andHarker 1991, Fuchsberger andLüthi 2007), branch-and-cut frameworks (Zwaneveld, Kroon, andVan Hoesel 2001, Ceselli et al 2008), branch-and-price approaches (Lusby 2008, Lin andKwan 2016), graph coloring algorithms (Cornelsen and Di Stefano 2007), and heuristics (Carey and Crawford 2007, Liu and Kozan 2011, Içyüz et al 2016.…”

High-Speed Railway EMUs’ Circulation Plan Optimization: A Two-Stage Optimization Algorithm Based on Column Generation

“…Borndorfer et al (2016) proposed a highly integrated generic hypergraph-based mixed-integer programming model for a rolling stock rotation problem in the context of long-distance passenger traffic between cities and an integrated algorithm for its solution, which can handle train composition, train unit maintenance, infrastructure capacities, and regularity aspects [28].…”