Linear Programming with Interval Coefficients

Abstract Many operational research optimization models, such as linear programming, assume that the data used to build a model is accurate, but in the real world most of these assumptions are only approximately true. In linear programming models, uncertainty is associated with the model coefficients during the formulation stage. A small number of papers discuss these models of linear programming with interval coefficients (LPIC). Using the method presented in paper [1], capable of solving linear programming problems with numerical intervals as intervals, we give in this paper a practical example, to demonstrate the use and the practicality of interval coefficients in linear programming models.