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

A Multi-Objective Vehicle Routing Problem (MO-VRP) was implemented with the aim of minimizing logistics costs, CO₂ emissions, and accident risks. Heterogeneous fleet comprising different vehicles powered by various energy sources, including battery, compressed natural gas, and diesel fuel, was considered. 
The Augmented Weighted Tchebycheff (AWT) method was selected to tackle the MO-VRP, and an enhanced Genetic Algorithm was employed as a heuristic to generate feasible solutions, which helped to warm-start the optimization process in the exact method when the model struggled to find solutions. 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. Finally, the approach proved to be useful in planning deliveries, considering the three objectives, due to its simplicity in generating solutions.