In order to solve the problem of multi-objective distribution system planning, in this work a methodology using as solution technique an Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed. This methodology considers location and capacity of new substations and feeders, and capacity increased of existing feeders and substations. For solving the problem, different mathematical models with two objective functions, are used. The application of different mathematical models seeks to have more tools to make decisions, in order to involve objective functions that directly influence the solution of the problem. The objective functions considered are: fixed costs, operative costs, fixed and operative costs, and network reliability (expected energy no supply). The set of constraints consider balance nodal equations, maximum allowable capacity of the system elements, the maximum allowable voltage drop and the radiality of the network. These mathematical models are integrated through the selection of trends; in other words, determination of common elements that are in the solution, thereby finding a topology common to all mathematical models. The proposed model is verified with distribution systems of different sizes. The results show the effectiveness of the method and these serve to identify elements in the planning study, seeking to satisfy at the horizon planning different proposed objectives.