In this paper, we study characterizations of minimal solutions to multi-objective optimization problems under with data containing the uncertainties defined in a given set. Firstly, we recall preliminaries of topological vector space ordered by a cone along with concepts related to the closedness, boundedness and properness properties of sets. Then, we consider properties of the nonlinear scalar function Gerstewitz in the topological vector space ordered by a solid cone and its generalizations. Finally, we introduce a concept of minimal solutions to the considered problems, and then based on properties of the generalization nonlinear scalar function, we establish characterizations of the minimal solutions. Besides, we give many examples to illustrate general concepts and properties to make the article easier to read.