Sustainable Multi-Modal Transportation and Routing focusing on Costs and Carbon Emissions Reduction

Transportation plays a critical role in supply chain networks, directly impacting cost efficiency, delivery reliability, and environmental sustainability. This study provides an enhanced optimization model for transportation planning, emphasizing environmental sustainability and cost-efficiency. An Integer Linear Programming (ILP) model was developed to minimize the total transportation costs by considering organizational and third-party vehicles' operational and rental costs while incorporating constraints on carbon emissions. The model incorporates multi-modal transportation routing and emission caps to select the optimized number of organizational and rental vehicles of different modes in each route to ensure adherence to sustainability goals. Key innovations include adding carbon emission constraints and optimizing route selection to reduce overall emissions. The model was implemented using the Gurobi solver, and numerical analysis reveals a trade-off between cost minimization and carbon footprint reduction. The results indicate that adopting tight environmental policies increases the costs by around 8% on average while more than 95% of the vehicles utilized will be rented. These insights provide actionable guidance for industries aiming to enhance both economic performance and environmental responsibility.