This paper shows an alternative method to find optimal solutions of a fuzzy linear programming (FLP) problems. The classical FLP problem is treated by using fuzzy restrictions in the form Ax les b where indicates a type-1 fuzzy set (T1 FS). The proposed approach uses joint A and b fuzzy parameters to solve a FLP model. Nonlinear membership functions are used to represent imprecisions in their parameters and the cumulative membership function (CMF) is used to solve the problem by means of an alpha-cut approach.
