Cities in various countries, including those in South America, are undergoing changes to improve living conditions. One such change involves acquiring products efficiently and promptly. This is the current reality of the globalized world. In this context of a consumerist society, locating sales centers and vehicle routing constitute a great support to optimize the process of serve people. This proposal develops an optimization model based on the mixed integer linear programming methodology and a new hybrid algorithm based on the k-means algorithm and local search. Therefore, they are a great contribution to the supply chain and environmental care because they not only optimize the process of serving customers by applying location-routing problems but also determine fuel consumption and measure the CO \(_{2}\) generation. The model implemented in GLPK (GNU Linear Programming Kit) obtains optimal results in small scenarios of up to 19 customers. For larger scenarios of 30 or 50 customers, the hybrid algorithm obtains good results in short processing times.