EURO 2024 Copenhagen
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2070. Bi-objective Algorithms for a Vehicle Replacement Problem including Budget Constraints and CO2 Emissions Minimization

Invited abstract in session TD-29: Exact Algorithms and Formulations for Combinatorial Optimization Problems, stream Combinatorial Optimization.

Tuesday, 14:30-16:00
Room: 157 (building: 208)

Authors (first author is the speaker)

1. Giulia Caselli
DISMI, Università degli Studi di Modena e Reggio Emilia
2. Joseph Hartman
UMass Lowell
3. Manuel Iori
DISMI, University of Modena and Reggio Emilia
4. Carlo Alberto Magni
Economics, School of Doctorate E4E (Engineering for Economics - Economics for Engineering) - University of Modena and Reggo Emilia
5. Giorgio Zucchi
Research & Development, Coopservice scpa

Abstract

The transportation sector, encompassing road (the primary source), sea, and air transport, accounts for 14% of global emissions over the last decade and around 25% of total greenhouse gas emissions in the European Union. This underscores the imperative for companies to prioritize transitioning to cleaner and greener modes of transport in their medium- to long-term vehicle investment plans. In this work, we address an original vehicle replacement problem with environmental concerns. A keep-or-replace decision must be made for every asset of the fleet in every time period while meeting budget constraints to minimize total discounted costs and CO2 emissions. Multiple options for replacement are given for every family of assets in such a way that fuel-based vehicles may be replaced by, for instance, electric and hybrid vehicles. The problem is inspired by a real-world industrial application in Italy and, because of its generality, can be used to model a large variety of further applications. We provide a dynamic programming model and integer programming formulations for the problem. Then, we compare the formulations and propose different bi-objective approaches to solve the problem in practice.

Keywords

Status: accepted

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