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To the best of author's knowledge, only three approaches are proposed in the literature to solve fully fuzzy linear fractional transportation problems. (Linear fractional transportation problems in which each known parameter is represented by a fuzzy number.) In this paper, it is pointed out that it is inappropriate to use any of these existing approaches as some mathematical incorrect assumptions are considered in these existing approaches. Also, a new approach (named as Mehar approach) is proposed to solve fully fuzzy linear fractional transportation problems. Furthermore, an exact fuzzy optimal solution of an existing fully fuzzy linear fractional transportation problem is obtained by the proposed Mehar approach. [ABSTRACT FROM AUTHOR]

To the best of author's knowledge, only one approach is proposed in the literature to solve fuzzy linear fractional minimal cost flow problems (minimal cost flow problems in which each known arc cost is represented either by a triangular fuzzy number or a trapezoidal fuzzy number). In this paper, the mathematical incorrect assumptions, considered in the existing approach to solve fuzzy linear fractional minimal cost flow problems, are pointed out. Also, by generalizing an existing approach for solving fuzzy linear fractional programming problems, an approach (named as Mehar approach) is proposed to solve fuzzy linear fractional minimal cost flow problems. Furthermore, two numerical examples are solved to illustrate the proposed Mehar approach. [ABSTRACT FROM AUTHOR]

In this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming (FFLP) problems with mixed constraints. By using the proposed method the fuzzy optimal solution of FFLP problems with mixed constraints occurring in real life situations can be easily obtained. To illustrate the proposed method a numerical example is solved. The proposed method can be easily applied to find the fuzzy optimal solution of FFLP problems occurring in real life situations. [ABSTRACT FROM AUTHOR]

In this paper, we discuss some new numerical methods to solve a fully fuzzy linear system (FFLS) with triangular fuzzy numbers of the form $$ ( {m,\alpha ,\beta }) $$. Almost every existing method that intends to solve a FFLS confines the coefficient matrix and the solutions to be non-negative fuzzy numbers. The main intent of the proposed methods is to remove these restrictions and widen the scope of fuzzy linear systems in scientific applications. The methods are illustrated with the help of numerical examples and are conceptually easy to understand and apply in real life situations. [ABSTRACT FROM AUTHOR]

In this paper, we discuss two new computational techniques for solving a generalized fully fuzzy linear system (FFLS) with arbitrary triangular fuzzy numbers (m, ɑ, β). The methods eliminate the non-negative restriction on the fuzzy coefficient matrix that has been considered by almost every method in the literature and relies on the decomposition of the dual FFLS into a crisp linear system that can be further solved by a variety of classical methods. To illustrate the proposed methods, numerical examples are solved and the obtained results are discussed. The methods pose several advantages over the existing methods to solve a simple or dual FFLS. [ABSTRACT FROM AUTHOR]