Improving the modified interval linear programming method by new techniques

In this study, we consider interval linear programming (ILP) problems, which are used to deal with uncertainties resulting from the range of admissible values in problem coefficients. In most existing methods for solving ILP problems, a part of the solution region is not feasible. The solution set obtained through the modified ILP (MILP) method is completely feasible (i.e., it does not violate any constraints), but is not completely optimal (i.e., some points of the region are not optimal). In this paper, two new ILP methods and their sub-models are presented. These techniques improve the MILP method, giving a solution region that is not only completely feasible, but also completely optimal.