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Optimizing Electric Vehicle Charger Locations for Ride-hailing Services through Discrete Simulation-based Optimization


19 avr. 2023   14h30 — 15h30

Tommaso Schettini HEC Montréal, Canada

Tommaso Schettini

We consider the problem of locating chargers for a fleet of electric vehicles operating a ride-hailing service with the objective of maximizing its operational profit. One of the main challenges of the problem lies in the fact that controlling the operation of the fleet is itself a stochastic dynamic problem, which makes a direct modeling approach extremely challenging. In practice, the most effective way of evaluating the performance of a particular charger configuration is to simulate its operation and measure its profit. Thus, the problem is formulated as a Discrete Simulation-based Optimization (DSO) problem. Due to the black-box nature of simulators, methods employed for DSOs tend to rely on iteratively sampling and partitioning the solution space so as to progressively concentrate the sampling effort on the most promising portions of the feasible space. To boost the effectiveness of such methods, it is fundamental to be able to quickly identify which portions of the feasible region are relevant to explore through an effective partitioning scheme. In our approach, we consider the use of a clustering approach to partition the search space of the DSO problem and identify high-quality regions of the search space.

Olivier Bahn responsable
Fausto Errico responsable
Carolina Osorio responsable


Activité hybride au GERAD
Zoom et salle 4488
Pavillon André-Aisenstadt
Campus de l'Université de Montréal
2920, chemin de la Tour

Montréal Québec H3T 1J4

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