2018-01 MSc assignment: Linehaul forecasting

This vacancy is for a graduation position at TNT. This will be a project supervised by both TNT and Ortec, who are working closely together on network design modelling for multiple years. Together we have developed strategic and tactical (planning) models that helps to develop TNT and its network of sorting hubs and linehaul transport.

As a Graduation student at TNT you will be part of an interesting company that is acting in the transport industry on a global scale. You will be part of a team that is evolving in a dynamic way to grasp the benefits of Big Data using OR techniques. With this assignment, you will be acting as a Graduation intern for Road Network Optimisation.

During this assignment, a forecasting model for the linehaul transport needs to be made. A similar model that forecasts the throughput at sorting hubs is already in place, but this model does not give enough detail about the expected number of trucks needed. Since the number of trucks is a big cost driver, an accurate forecasting model will have a large added value and is therefore very important for TNT.

The following activities will be part of the internship:

  • Discuss and understand wishes about the forecast from different stakeholders
  • Evaluate different methods for forecasting of linehaul transport
  • Implement an accurate forecasting model
  • Validate the results and evaluate with stakeholders

As depicted by the activities, the challenge with this internship is to make a model that is mathematically of high standard, but also gives practical added value to the business.

Who you are

We are looking for someone who is enthusiastic to take up the challenge of developing a forecasting model and who knows how to combine business requirements with modeling necessities. Some characteristics that should apply to you:

  • You are a student in the master phase of your study in the areas of Econometrics, Operations Research, Logistics, Data-Science
  • You have affinity with data science and/or supply chain optimization
  • You are able to work with large datasets
  • You are capable of programming in “R” or another programming language

What we offer

At TNT, we want the best for our employees, since a good working environment supports the happiness and quality of the work. For this position, you can expect:

  • A pleasant, open, informal atmosphere
  • Inspiring, smart and enthusiastic colleagues
  • Early responsibility

 For more information, contact M.R.K. Mes (m.r.k.mes@utwente.nl).