The electrification of heavy-duty transport is an important contributor to a more sustainable future, a transition that requires more careful planning of how to operate the vehicles. One challenge to address is how to efficiently share charging resources among vehicles to avoid waiting times and unnecessary power peaks.
- Speaker
- Date
- Monday 6 Oct 2025, 14:00 - 15:00
- Type
- Seminar
- Room
- TBA
- Building
- E Building
In a joint project with the truck manufacturer Scania, we investigate the potential of introducing bookable time slots at the chargers to tackle this challenge. To investigate the computational aspects of such an introduction, this paper studies the Electric Vehicle Routing Problem with Time Windows (EVRPTW) and capacitated charging resources available only during specific time slots. This limited availability significantly changes which routes are feasible compared to in the standard EVRPTW.
To efficiently solve the problem, we build upon the generic branch-price-and-cut framework GCG which is part of the SCIP Optimization Suite. We extend GCG with both a customised labeling algorithm for solving the pricing problem and problem-specific pricing for integrality. The latter is a heuristic designed to generate columns that are likely to be a part of high-quality integer solutions.
The heuristic builds on the more generic LNS-heuristic IPColGen which has a theoretical foundation, leveraging optimality conditions for integer programmes. Given a set of columns that constitute an integer partial solution, our heuristic aims at finding columns that complement this solution. This is done by adapting the pricing problem with respect to the partial solution, linear programme dual information as well as previously generated columns in the heuristic.
Preliminary computational results show that using the heuristic leads to improvements in terms of identifying high-quality integer solutions early in the process.
About the speaker
Lukas Eveborn is a PhD student at Linköping University since spring 2023 and a member of the research group Mathematics and Algorithms for Intelligent Decision-Making, led by Professor Elina Rönnberg.
He works within the Condore project — a collaboration between truck manufacturer Scania, the Division of Vehicular Systems at LiU, and the research group.
His research focuses on route planning for heavy electric vehicles, with a particular emphasis on improving optimisation methods in column generation and route planning to address the challenges of electrification.
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Lunch will be provided (vegetarian option included).
For more information please contact the Secretariat Econometrics at eb-secr@ese.eur.nl
