Mixed-Fleet Goods-Distribution Route Optimization Minimizing Transportation Cost, Emissions, and Energy Consumption

Mohammad Javad Jafari, Luca Parodi (), Giulio Ferro, Riccardo Minciardi, Massimo Paolucci and Michela Robba ()
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Mohammad Javad Jafari: DIBRIS—Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, GE, Italy
Luca Parodi: DIBRIS—Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, GE, Italy
Giulio Ferro: DIBRIS—Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, GE, Italy
Riccardo Minciardi: DIBRIS—Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, GE, Italy
Massimo Paolucci: DIBRIS—Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, GE, Italy
Michela Robba: DIBRIS—Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, GE, Italy

Energies, 2025, vol. 18, issue 19, 1-26

Abstract: At the international level, new measures, policies, and technologies are being developed to reduce greenhouse gas emissions and, more broadly, air pollutants. Road transportation is one of the main contributors to such emissions, as vehicles are extensively used in logistics operations, and many fleet owners of fossil-fueled trucks are adopting new technologies such as electric, hybrid, and hydrogen-based vehicles. This paper addresses the Hybrid Fleet Capacitated Vehicle Routing Problem with Time Windows (HF-CVRPTW), with the objectives of minimizing costs and mitigating environmental impacts. A mixed-integer linear programming model is developed, incorporating split deliveries, scheduled arrival times at stores, and a carbon cap-and-trade mechanism. The model is tested on a real case study provided by Decathlon, evaluating the performance of internal combustion engine (ICE), electric (EV), and hydrogen fuel cell (HV) vehicles. Results show that when considering economic and emission trading costs, the optimal fleet deployment priority is to use ICE vehicles first, followed by EVs and then HVs, but considering only total emissions, the result is the reverse. Further analysis explores the conditions under which alternative fuel, electricity, or hydrogen prices can achieve competitiveness, and a further analysis investigates the impact of different electricity generation and hydrogen production pathways on overall indirect emissions.

Keywords: hybrid fleet; hydrogen fuel cell; carbon cap-and-trade; routing optimization; mixed-integer linear programming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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