This paper presents en algorithm for solving interval linear programming problems. The algorithm is a finite iterative method, which in each iteration solves a full row rank interval linear progranming problem, with only one additional constraint. The solution and/or problem chosen appears to be conputationally more efficient than that in the Ben-Israel and Robers algorithm.

Abstract In this paper, we use interval-valued fuzzy numbers to fuzzify the crisp linear programming to three cases. The first case, we use intervalvalued fuzzy numbers to fuzzify the coefficients in the objective function. We get a linear programming in the fuzzy sense. The second case, we use interval-valued fuzzy numbers to fuzzify the coefficients akj in the constraints about xj, j = 1, 2, ...

Matrix game theory is concerned with how two players make decisions when they are faced with known exact payoffs. The aim of this paper is to develop a simple and an effective linear programming method for solving matrix games in which the payoffs are expressed with intervals. Because the payoffs of the matrix game are intervals, the value of the matrix game is an interval as well. Based on the...

In this paper, we introduce a class of fuzzy linear programming problems and de ne the concepts of feasible and satis cing solutions—the necessary tools for dealing with such problems. In this way, we show that the class of crisp (classical) LP problems can be embedded into the class of FLP ones. Moreover, for FLP problems we de ne the concept of duality and prove the weak and strong duality th...

In many real world problems, system parameters or model coefficients may be bounded between lower and upper bounds due to a variety of uncertainties. Over the past decades, intensive research efforts have focused on interval linear programming (ILP) to tackle such uncertainties. As one of the most popular methods for solving ILP problems, Two-Step Method (TSM, proposed by Huang et al. in 1995) ...

The equivalence between the interval-valued fuzzy set (IVFS) and the intuitionistic fuzzy set (IFS) is exploited to study linear programming problems involving interval uncertainty modeled using IFS. The non-membership of IFS is constructed with three different viewpoints viz., optimistic, pessimistic, and mixed. These constructions along with their indeterminacy factors result in S-shaped memb...

This paper discusses a class of linear programming problems with interval coefficients in both the objective functions and constraints. The noninferior solutions to such problems are defined based on two order relations between intervals, and can be found by solving a parametric linear programming problem. Considering the uncertain returns of assets in capital markets as intervals, we propose a...

In previous studies, it is pointed out that in several situations it is better to use interval-valued fuzzy numbers instead of triangular or trapezoidal fuzzy numbers. But till now, there is no method that deals with the sensitivity analysis of such linear programming problems in which all the parameters are represented by interval-valued fuzzy numbers. In this paper, a new method is proposed f...

The interval linear programming (IvLP) 1 is a method for decision making under uncertainty. A weak feasible solution to IvLP is called weakly optimal if it is optimal for some scenario of the IvLP. One of the basic and difficult tasks in IvLP is to check whether a given point is weak optimal. In this paper, we investigate linear programming problems with interval right-hand side. Some necessary...