EURO 2024 Copenhagen
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2783. A two-stage stochastic programming approach for an electric fleet composition and mix vehicle routing problem.

Invited abstract in session TD-35: Location and transportation problems under uncertainty, stream Stochastic, Robust and Distributionally Robust Optimization.

Tuesday, 14:30-16:00
Room: 44 (building: 303A)

Authors (first author is the speaker)

1. Paolo Beatrici
Department of Management, Information and Production Engineering, University of Bergamo
2. Francesca Maggioni
Department of Management, Information and Production Engineering, University of Bergamo
3. Sebastian Birolini
Department of Management, Information, and Production Engineering, University of Bergamo
4. Paolo Malighetti
Department of Management, Information and Production Engineering, University of Bergamo

Abstract

In this talk we consider a fleet composition and delivery routing problem, performed by a heterogeneous fleet of both conventional and electric vehicles under uncertain demand. Multi-trips for recharging operations of the electric vehicles to the central depot are considered. The problem is modeled as a two-stage stochastic mixed integer program where the first stage decisions are related to the selection of the vehicles which compose the fleet while second stage decisions concern the routing to satisfy the uncertain customer demand. The aim is the minimization of total operation costs due to the initial acquisition of fleet components, the travel time of each vehicle and an extra penalty cost in case of unserved customers. A tradeoff between cost and emissions is evaluated to analyze the impact of the selection of electric vehicles in the delivery fleet. Scenarios representing the stochasticity in customers’ demand are generated through a kernel density estimation approach. Computational experiments are carried out on instances based on real data of a large Italian delivery company. The impact of stochasticity on demand is examined through stochastic measures. Some managerial insights are finally discussed.

Keywords

Status: accepted

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