Editorial: Special issue on practical value of railway operations research

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Introduction

Railway systems continue to play a vital role in a multimodal transport market of goods and passengers, due to their advantages in volume, efficiency speed, and environment friendliness. In the meantime, railway systems are facing increasing competition from other transport modes like air traffic and road transport, where automation is reaching the potential for disruptive, system wide changes. This yields a continuous pressure for railway operators for improving the service quality and operation/economic efficiency of railway systems.

Although researchers in both universities and institutes of applied research have been often collaborating with industries related to railway operations, and they are eager to contribute their solutions to real world problems, there is still quite a big gap between academic state of the art, and industrial state of practice. Few success stories emerge related to railway operations research which can actually deliver the promised value.

This special issue aims at providing an overview of those latter, collecting success stories where operations research has been instrumental for improving the quality of operations and services of railway systems, as assessed in practice. Due to some limitations, the special issue cannot cover all applied operations research achievements and the aspects of how operations research can be helpful for practical operations, but aims to be an example in attracting more attention from the academia to consider the possibility of transforming excellent theories and models not only in high level papers, but also in implementable, actionable solutions of practical issues.

Section snippets

Contributions

Liebchen and Schülldorf (2019) tackle directly the question on why optimization approaches in railway industry might fail or succeed. They resort to a set of interviews to test the reasons why many projects, with excellent potential from a purely academic point of view, did not manage to be successfully used in practice. The survey reports that a set of factors, namely capacity for validation, management attention, quality of input data, and “moving target” objectives, are critical for a

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