A Vehicle Routing Problem for Human-Centered Electric Mobility
A new algorithm balances EV range, charging stops, and human preferences.
A team of researchers—Mostafa Emam, Björn Martens, Thomas Rottmann, and Matthias Gerdts—has published a paper on arXiv introducing the Electric Mobility Dial-a-Ride Problem (EM-DARP). This new model extends the existing Electric Vehicle Dial-a-Ride Problem (EV-DARP) to better accommodate human-centered mobility services. The core challenge involves routing a heterogeneous fleet of electric vehicles (EVs) to fulfill customer requests that include specific DARP (Dial-a-Ride) and mobility-related specifications, all while incorporating necessary visits to charging stations between trips.
The problem is formulated as a Mixed-Integer Linear Program (MILP), a standard optimization approach for complex routing problems. The researchers then solved the MILP for a number of curated evaluation scenarios to demonstrate its practical applicability. The work, detailed in a 7-page paper with 5 figures, sits at the intersection of systems and control, combinatorics, and optimization. The paper is available on arXiv under the identifier 2604.22737 and has been submitted to the Electrical Engineering and Systems Science category.
- EM-DARP extends EV-DARP to prioritize human-focused mobility needs alongside EV range constraints.
- The model uses a heterogeneous EV fleet and includes mandatory charging station visits within routes.
- Formulated as a Mixed-Integer Linear Program (MILP) and validated on curated scenarios for practical use.
Why It Matters
This model could enable more efficient and user-friendly electric ride-sharing services, balancing range anxiety with passenger convenience.