Multi-Objective Approach for Solving VRP with a Heterogeneous Fleet Powered by Different Energy Sources

A solution approach to the Multi-Objective Vehicle Routing Problem (MO-VRP) was applied to a real-case, aiming to minimize logistics costs, CO₂ emissions, and accident risks. Heterogeneous fleet comprising different vehicles powered by various energy sources, e.g. battery, compressed natural gas, and diesel fuel. The Augmented Weighted Tchebycheff (AWT) method was selected to tackle the MO-VRP, and an enhanced Genetic Algorithm was employed to generate feasible solutions, which helped to warm-start the optimization process in the exact method. The results showed that diesel trucks were the most economically viable, but Alternative Fuel Vehicles (AFVs) were preferred when prioritizing CO₂ emissions, achieving a 90% reduction. However, this lead to a 35% increase in logistics costs. When accident risks were prioritized, they were reduced by 55%, while logistics costs enhanced by 60%. Finally, the approach proved to be useful in planning deliveries, considering the three objectives, due to its simplicity in generating solutions.