Smart maths helps rail passengers and train personnel Tuesday, 21 October 2014
How can smart algorithms help restore rail services for travellers? Why isn’t it effective just to have a simplified train schedule with a limited number of routes? And how does smart maths contribute to increased job satisfaction among railway personnel? In his thesis Crew Management in Passenger Rail Transport PhD candidate Erwin Abbink from Rotterdam School of Management, Erasmus University (RSM) demonstrates how advanced mathematics helps the Dutch railway company Nederlandse Spoorwegen (NS) to create a better timetable, even when there are disruptions to rail services.
Algorithms as an export product
The NS performs approximately 23,000 tasks every day, from providing a single train journey to checking tickets on a particular route. Drafting a timetable for all these tasks requires many factors to be taken into account, concerned with health and safety, shift work, a diversified work roster and a fair distribution of routes, especially where some have higher incidences of aggression from passengers. After rail unions opposed the introduction of repetitive and simplified train routes, the company adopted the use of algorithms optimised by Abbink instead, and these are discussed in his thesis.
Abbink’s algorithms are not only used by NS; they have also been implemented by other rail companies such as London Underground and the state-run Danish railways DSB. The methods are also finding new applications in rail transport.
Hours, not months
These new mathematical methods make it possible to plan personnel services for ticket collectors and engineers in terms of hours instead of months, as was previously the case. Mathematical techniques are also increasingly used for rapid adjustments to the rail timetable during wintry weather, or for quick redeployment of train personnel in the event of disruption, allowing trains to move more efficiently and giving employees more job satisfaction. At the same time there are fewer cancellations, which results in a better service for passengers.
Erwin Abbink, together with a number of colleagues and researchers, has won a number of prizes for his work with NS, including the INFORMS Franz Edelman award in 2008 for the application of mathematics to expedite and improve complex timetables. Most of his research was conducted with networks of researchers, logistics experts and ICT companies. In addition to researching for his doctorate at EUR, he also leads the NS Innovation Group.
Abbink will defend his thesis in the Erasmus University Rotterdam Senate Hall on Friday, 24 October 2014. His thesis promotors are Prof. Leo Kroon and Prof. Albert Wagelmans, and his co-supervisor is Dr Dennis Huisman. Other members of the doctoral committee are Prof. Will Bertrand (Eindhoven University of Technology), Prof G. T. Timmer (VU University Amsterdam) and Prof Erik van Heck from RSM.
The deployment of drivers and conductors on trains in NS is essential for delivering services to travellers, and forms a large part of the company's costs. In his thesis, Abbink presents various models and algorithms to support the planning and adjustment of such mobile workers. He also gives a more managerial consideration of the related change process and lessons learned from the introduction of these systems into practice.
Their introduction has resulted in a more stable and satisfying relationship between NS and its staff. In addition, planning is a quicker process, taking just a few hours, and the analysis of scenarios has saved a lot of time for the company by making it possible to adjust employment contracts.
As a result of the algorithms, Abbink can also quickly customise rail services; for example if wintry conditions are expected. Finally, it is now also possible to adjust staffing on the day using advanced decision support systems meaning fewer delays and cancelled trains and greater adaptability.
About the author
Erwin Abbink graduated with a MSc in Econometrics from the University of Groningen in 1995, followed by an MSc in Information and Knowledge technology from Middlesex University in London in 2000.
He is currently a Consultant Manager for Innovation at NS, with a focus on decision support systems and advanced analytics. He has a broad experience in rail logistics and in disruption management for railway systems. He has published papers in journals such as Transportation Science, Interfaces, and Public Transport on rolling stock assignment, shunting, crew scheduling, crew rostering and crew dispatching.
In 2004 he was a finalist in the Daniel H. Wagner Prize for Excellence in Operations Research Practice after co-authoring the paper Reinventing Crew Scheduling at Netherlands Railways. In 2008 he was winner of the Franz Edelman Excellence in Practice award after co-authoring The New Dutch Timetable: The O.R. Revolution. In 2009 he was awarded with the Best Applied Paper Award at the BNAIC for Actor-agent based approach to train driver rescheduling. His main research interest during his work at NS is in applying operations research in practice.
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