Join us for an EI-ERIM-OR seminar.
- Speaker
- Coordinator
- Coordinator
- Date
- Friday 17 Oct 2025, 12:00 - 13:00
- Type
- Seminar
- Room
- ET-14 (E Building)
Abstract
In this talk, I'll address the Capacitated Vehicle Routing Problem with Stochastic Demands (CVRPSD), in which routes are planned in advance and recourse actions are taken to ensure demand fulfillment. The recourse actions are based on policies such as replenishment trips to backlogging demand. We present a mathematical definition of different recourse policies and Mixed-Integer Programming formulations that explicitly model them in a closed formulation for the Vehicle Routing Problem. These formulations allow us, for the first time, to solve instances of the CVRPSD to optimality with the use of a general-purpose solver. Based on these formulations, we present a series of Branch-and-Cut methods that are, at the same time, computationally efficient and, in terms of implementation, accessible for a wide range of practitioners and researchers. We finally discuss the performance of our methods and evaluate recourse policies from a managerial perspective, quantifying the cost of conservative strategies and the value of the stochastic approach.
Bio
Caio Tomazella is a postdoctoral researcher at the Federal University of São Carlos and, since September 2025, a visiting researcher at Erasmus University Rotterdam, with his current work being focused on exact methods for stochastic vehicle routing problems. His academic background includes B.Sc. and M.Sc. degrees in Industrial Engineering and a Ph.D. in Computer Science and Computational Mathematics from the University of São Paulo, Brazil. During his doctoral studies, he also spent a year at HEC Montréal as a visiting student. His research has been published in journals such as the International Journal of Production Research and the European Journal of Operational Research, and he has presented his work at several national and international Operations Research conferences. Beyond vehicle routing, his interests include scheduling and lot-sizing problems and stochastic programming.
