Using linear ranking functions for solving bounded linear programming with fuzzy cost coefficients based on dual simplex method and its applications

In some of optimization problems, the coefficients involved in the objective functions are imprecise in nature and have to be interpreted as fuzzy numbers to reflect the real world situation. Some authors used linear programming with fuzzy numbers as an auxiliary problem for solving linear programming with fuzzy variables based on primal simplex method. However, their approach is not efficient when some or all of decision variables are bounded in the auxiliary problem. Thus, in this paper by a natural extension of the results in deterministic linear programming and based on a certain linear ranking function, we obtain some new results leading a new method namely bounded dual simplex method to overcome this shortcoming. The advantage of this method is its simplicity inprogramming and computation.

کلیدواژه ها:

Fuzzy optimization ، ranking functions ، fuzzy numbers ، bounded dual simplex method