This paper presents a model formulation for the multiobjetive optimization of transportation costs, inventory costs and service level for the goods distribution process. The multiobjective model is composed by two objective functions, in which the transportation and inventory cost are optimized using the Inventory Routing Problem (IRP) and the service level is optimized using the number of accomplished time windows for the vehicles in the routing process. The model is solved using the Nondominated Sorting Genetic Algorithm II (NSGAII), implementing a novel representation of the chromosome, which allows assigning inventory and routes simultaneously. The algorithm allows calculating the Pareto Frontier for the analyzed distribution case, observing good qualities in the solution, compared with what is found in scientific literature.