A Mixed-Integer Linear Programming Model for Green Vehicle Routing Problems
DOI:
https://doi.org/10.64137/31082637/IJMAR-V1I2P105Keywords:
Green Vehicle Routing Problem (G-VRP), Mixed-Integer Linear Programming (MILP), Sustainable Logistics, Emission Reduction, Fuel Consumption Optimization, Eco-Friendly RoutingAbstract
The growing environmental impact of transportation and logistics has prompted increasing attention to sustainable routing practices. This study addresses the Green Vehicle Routing Problem (G-VRP) by developing a Mixed-Integer Linear Programming (MILP) model that simultaneously minimizes travel distance, fuel consumption, and carbon emissions while satisfying operational constraints such as vehicle capacity, route feasibility, and time windows. The proposed model is tested on benchmark instances and evaluated against traditional vehicle routing solutions, demonstrating substantial reductions in fuel use and environmental emissions without compromising service efficiency. Computational experiments highlight the trade-offs between operational efficiency and environmental sustainability, offering actionable insights for fleet managers seeking to implement eco-friendly routing strategies. The results also identify the scalability challenges and potential for integrating heuristic methods in larger transportation networks. This research contributes to both the theoretical understanding of green routing optimization and practical applications in sustainable logistics, providing a foundation for future studies on multi-objective, real-time, and electric vehicle routing systems.
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