Optimization for Evaluating the Practical Capacity of a Transshipment Yard

TL;DR

This paper presents a MILP optimization model to evaluate and enhance the practical capacity of transshipment yards, enabling increased train services without timetable disruptions, validated on a real Italian yard with promising results.

Contribution

It introduces a novel MILP-based model for assessing and optimizing transshipment yard capacity considering operational constraints and future investment scenarios.

Findings

Doubling the current train services is feasible with proper investments.

The model provides detailed routes and schedules for operational planning.

Validation on a real yard confirms the model's practical applicability.

Abstract

In order to increase rail freight transportation in Italy, Rete Ferroviaria Italiana (RFI) the Italian railway infrastructure manager, is carrying out several investment plans to enhance the Transshipment Yards, that act as an interface between the rail and road networks. The need is to increase their practical capacity, i.e. the maximum number of train services that can be inserted without altering the current timetable while respecting all relevant constraints. Several factors influence the practical capacity of a transshipment yard: physical resources (such as tracks and vehicles for loading/unloading); constraints on the possible time slots of individual operations; constraints on the length of time a train must stay in the yard, that follow from both timetable requirements that are settled by the (prevalent) main line and from administrative and organisational issues in the yard. In this paper, we propose a MILP-based optimization model that is based on the solution of a suitable saturation problem, that deals with all these constraints and that can be used for evaluating the practical capacity of a transshipment yard both in its current configuration and in any plausible future configuration. The model provides operational details, such as routes and schedules, for each train service, and allows to impose periodic timetables and schedules that keep the daily management of the yard easier. Both the model and its solutions are validated on a real Italian transshipment yard, located at Marzaglia, on different scenarios corresponding to different investment plans of RFI. The results show that proper investments allow to get a feasible timetable with a period of 24 hours with doubles the number of current train services.