Customizable route planning (CRP) @ ORTEC https://customerimages.magnet.me/71b23818cd3507774174f18b73ead7d6_1170_418.jpg?fit=crop https://magnet.me/a/company/ortec/opportunity/14558/customizable-route-planning--crp-?lang=en As a Graduation student: Customizable route planning (CRP) at ORTEC you will be part of a unique organization and team! What you do Managing a flee...

Customizable route planning (CRP)

Customizable route planning (CRP)

Internship

Zoetermeer, Netherlands

Negotiable

As a Graduation student: Customizable route planning (CRP) at ORTEC you will be part of a unique organization and team!

What you do

Managing a fleet of trucks (like other use cases in logistics) often involves vehicle routing problems (VRPs). This means, a huge amount of shortest path computations must be performed as efficient as possible. Luckily, the research of the last decade has provided great progress in the area of route planning algorithms. Current algorithms are able to generate distance tables for 10000 random addresses in continental size road network within even 10 seconds. A downside of this technology is, however, that a very costly preprocessing of the road network is necessary whenever the underlying cost model changes. So, efficient planning is possible but with a considerable lack of flexibility; because changing the cost model can even take hours.

This is where one of the hottest current route planning algorithms, known as customizable route planning (CRP), enters the stage. CRP splits the costly preprocessing of the road network into an expensive cost-model-independent and a much cheaper cost-model-dependent part. Changing the cost model of a continental size road network is now possible in a couple of seconds instead of hours. However, CRP cannot be applied to the area of logistics yet, as some open issues have to be solved before.

So, ORTEC is looking for a student doing research on CRP within a thesis project. Issues to consider are

  • the efficient computation of distance tables with CRP,
  • time-dependent route planning with CRP,
  • their combination; that is, the generation of time-dependent table-like structures with CRP.

Both, the efficient computation of distance tables and time-dependent route planning are especially interesting for logistics. Distance tables, on the one hand, help to solve VRPs faster. Time-dependent route planning, on the other hand, solves a generalized shortest path problem that is able to deal with regular effects like, e.g., congestions during rush hours, city centers being blocked at certain times of day, or tunnels that are forbidden for certain types of load at certain times.

With this thesis project, ORTEC offers the opportunity to work on a very interesting algorithmic problem with practical relevance under supervision of experts in the field.

Who you are

  • a student in computer science or a related field
  • good at algorithms,
  • interested in the implementation of algorithms and their practical applicability,
  • good at programming and like to write efficient code,
  • good at C++ or willing to learn it,
  • like experimenting,
  • want to do real research.

What we offer

  • A pleasant, open, informal atmosphere
  • Early responsibility
  • Inspiring, smart and enthusiastic colleagues
  • Ample opportunities to develop yourself (internationally)
  • Excellent pay and conditions
  • Active employee association

What to expect

We help you to thrive in your field of expertise. We offer development programs, tailored to your individual needs and function requirements, including opportunities to attend courses and seminars. We offer challenging practical hands-on experience, with opportunities to work abroad. We operate a flat organizational structure that keeps communication lines short. The atmosphere is open, informal, cooperative and positive. We employ over 800 people in the Netherlands, Belgium, Germany, France, the U.K., Romania, Italy, Poland, the U.S., Australia, and Brazil. Visit our website ortec.com to learn more about our solutions, clients’ experiences and ORTEC Living Data.

Acquisition to this vacancy is not appreciated.