Real-world case study: how do you factor en-route charging into route planning?

Challenge: Incorporating charging into existing route algorithms

CQM previously developed an algorithm—RitOpt—for its partner Evo-IT to optimally plan delivery and collection routes across multiple fleets. A question that recently arose was whether this algorithm is also suitable for electric vehicles—specifically, how to efficiently factor in mid-trip charging stops during the planning process.

Implementing a basic distance constraint (such as a maximum number of kilometers per trip) was straightforward. However, actively modeling charging stops as part of the route requires a different approach. During the Modelling Week, students investigated whether this extension could be accommodated within the algorithm's existing structure or if fundamentally different choices were required.

After a brief introduction on Monday, the students independently tackled the issue. Within a week, they structured the problem, made decisions regarding their approach, and presented their solution on Friday. Interaction for clarification and reflection was limited throughout the week, mirroring how consultancy projects unfold in practice.

It was striking that their proposed solution closely resembled techniques CQM already employs for scheduling breaks within routes. This instilled confidence in their line of reasoning while simultaneously yielding new insights for further development.

“The one-on-one sessions with students are always valuable: there is great enthusiasm, and it is interesting to see how they approach the issue and set priorities.”

Moreover, during the closing session on Friday, it was striking how interested the students were in day-to-day practice. Many of them actively sought out conversations with companies to learn more about the work behind the case studies.

What are the benefits?

For CQM, the Modelling Week offers an opportunity to present a well-defined, topical case to a fresh group of thinkers. Although it is not a research project in the strict sense, it helps us better gauge the complexity of a new component and gain inspiration for next steps.

The insights gained from this edition will be incorporated into the further development of the algorithm. In this way, the collaboration helps us future-proof route planning in a rapidly electrifying world.
And perhaps even more importantly: it confirms that CQM continues to invest in innovation, even in the absence of a specific client request. New ideas often emerge precisely where curiosity and expertise meet.

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