Train Unit Scheduling Optimization Considering Unit Ordering

TL;DR

This paper introduces an enhanced train unit scheduling model that incorporates unit ordering and direction parameters, effectively providing order information and preventing station blockage in railway scheduling.

Contribution

The study develops a novel integer multicommodity flow model for train unit scheduling that includes unit ordering variables and train direction parameters, addressing station blockage issues.

Findings

Model successfully provides train unit order information.

Prevents station blockage in scheduling.

Effective on both artificial and real-world data.

Abstract

The train unit scheduling problem (TUSP) is an important part of the scheduling process for passenger railway operators. Currently, scholars in various countries have proposed a variety of optimization models based on specific local railway situations and scheduling needs. This research investigates the train unit scheduling problem in the UK. We propose an Enhanced Train Unit Scheduling Problem with Unit Ordering based on existing integer multicommodity flow models. We innovatively introduce unit ordering variables representing the order in which train units are coupled for serving the same trip as well as train direction parameters so that our model can provide unit order information and avoid unit blockage in stations. We present experimental results based on three different sizes of artificial data, as well as real-world data based on the Trans Pennine Express' Anglo-Scottish route. The experimental results showed that our model is able to provide the ordering information corresponding to each train unit and prevents the blockage in the station.