Marginalization studies of a population are tools that enable the Mexican government to understand and compare the socio-demographic situation of different regions of the country. The goal is to implement effectively various programs of social or economic development whose aims are to fight against the population’s lag, which has affected the quality of life of Mexican citizens. In this paper, a multi-criteria approach for ranking the municipalities of the states of Mexico by their levels of marginalization is proposed, and the case of Jalisco, Mexico, is presented. The approach uses the ELECTRE III method to construct a medium-sized valued outranking relation and then employs a new multi-objective evolutionary algorithm (MOEA) based on the nondominated sorting genetic algorithm (NSGA) II to exploit the relation to obtain a recommendation. The results of this application can be useful for policymakers, planners, academics, investors, and business leaders. This study also contributes to an important, yet relatively new, body of application-based literature that investigates multi-criteria approaches to decision-making that use fuzzy theory and evolutionary multi-objective optimization methods. A comparison of the ranking obtained with the proposed methodology and the stratification created by the National Population Council of Mexico shows that the methodology presented is consistent and yields reliable results for this problem.