Mathematical Model for Special Capacitated Vehicle Routing Problem Considering Environmental Factors

This research proposes a mathematical model for the capacitated vehicle routing problem with special operational constraints, incorporating environmental considerations in a real-world beverage distribution case study. The model determines the optimal selection of vehicles, routes, truck types, and loading configurations to minimize total carbon dioxide (CO₂) emissions while satisfying practical capacity and operational requirements. The proposed model is formulated as a mixed integer linear programming problem and solved using the GUROBI Solver. Computational results indicate that the optimized routing plans achieve a minimum total emission of 145.70 kgCO₂eq/L, outperforming the company’s existing delivery strategy. Furthermore, experiments using daily demand data over a 10-day period demonstrate an average CO₂ emission reduction of 7.96%, implying improved fuel efficiency and more sustainable transportation operations. These findings highlight the practical relevance of applying exact optimization models to address current challenges in emission-aware logistics planning. Future research may extend the proposed framework to larger-scale networks, multi-objective formulations, and additional environmental indicators to further enhance decision-making in sustainable transportation systems.