Efficiently distributing goods and materials is a vital aspect of logistics and supply chain management. In this paper, we develop a clustering mathematical programming model to consolidate the transportation logistics of an established set of routes. Each route has a determined weight and volume of transported goods per week. In this context, we study the impact of consolidating routes to procure the manufacturing facilities by leveraging the weight and volume of the established routes. To assist during the decision process, the model has different parameters that the decision maker can adjust in order to better model the supply chain under study. Furthermore, a branch and price algorithm is developed and tested to solve the real-world instances inspired in the automotive sector with up to 900 suppliers and 50 manufacturing facilities. Thus the decision tool has been validated in a first-tier supplier of the automotive industry.