A New Approach for Solving Linear Programming Problems with Uncertainty Coefficients

Abstract

In this paper, this algorithmic solution based on rough interval coefficients for uncertainty parameters is developed using the lower and upper interval (LILP) and (UILP) approaches. We proposed method addresses the uncertainty (rough interval) Programming (RIP) problem, in which the coefficients of the objective function and constraints are characterized as uncertainty intervals. An algorithm gives an efficient decision support tool structure for solving linear programming problems characterized by uncertain data. It is shown that the solutions of the related crisp problems, namely the Upper Crisp Interval  linear  programming Problem (UIP(λ)) and the Lower Crisp Interval linear programming Problem (LIP(λ)), The solution of the (UIP(λ))  and (LIP(λ)) are depends on the value  of form limits of the interval solution of the RIP problem and its optimal solution, the solution of the (UIP(λ))  and (LIP(λ))    are depends on the value (   which decision maker. The applicability of the proposed approach is verified through a numerical example.