Multi-objective optimization is a way to manage multiple objectives in analytical decision support systems. However, for real-life problems, different types of uncertainty often become prominent when defining the model. In this paper, we analyze these different types of uncertainties and suggest a suitable typology for a decision process based upon multi-objective optimization models. Uncertainty analysis can be performed based on the proposed typology; therefore, this analysis provides the necessary support for a decision maker in the identification the crucial uncertainty in the decision process.