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The global supply chain relies on road, land, and air transport, significantly contributing to greenhouse gas emissions. Various measures have been proposed to reduce these emissions, including energy taxes, environmentally friendly vehicles, and optimized transportation loads. Current optimization mainly considers fixed loads and vehicle types to reduce CO2 emissions. However, dynamic loads in distribution networks and their interactions with factors like distance and vehicle type have not been studied. The present work contributes by (a) extending a vehicle routing problem (VRP) database to include vehicle type and load size data; (b) developing a mathematical model for emissions based on traveled distance, vehicle type, and load size; (c) creating a multivariate database of the emissions considering optimal routing; and (d) analyzing the database to identify key factors influencing emissions. A factorial analysis determined that vehicle type, load size, and traveled distance are the main factors associated with CO2 emissions. By coding and rearranging the database considering three levels for each main factor, a 3k full factorial design was developed to analyze the interactions of these factors and their effect on CO2 emissions. The results of the analyses corroborate that optimizing vehicle utilization and minimizing routes, which depend on optimal load, distribution routes, and infrastructure planning, are recommended actions to reduce emissions. |
