عنوان مقاله [English]
Supply chain management (SCM) is an important subject in competitive economics. A supply chain includes all activities related to the flow of goods from the raw material through to the customer, as well as information flow.
Determination of appropriate suppliers in SCM is very significant. Therefore, a problem is defined, named the supplier selection, to evaluate each supplier. Supplier selection is a multi-criteria decision making (MCDM) problem. In MCDM
problems there are two important issues: the method that should be selected and the criteria. A decision maker needs to use one of the MCDM methods to solve a problem. In this paper, a multi-objective model is proposed for the supplier selection problem. Objective functions, such as minimization of cost, and maximization of quality level and on-time delivery are considered criteria in this model. Since the parameters of the model cannot be predicted precisely, the fuzzy theory is used. Fuzzy set theory has been widely used to solve many complex problems. This theory has considered effective methods to manage both vagueness and uncertainty in different problems. In our proposed model, the parameters of objective functions, the demand constraint and all decision variables are defined as triangular fuzzy numbers. This type of problem, in which all parameters and variables are defined as fuzzy numbers, is called a fully fuzzy problem. So, our proposed model is a multi-objective fully fuzzy linear programming (MOFFLP) problem, and one of the most difficult to solve. In this study, for solving this MOFFLP problem, first a method is used which finds the fuzzy optimal solution of FFLP problems. This method has proved its efficiency in several problems and we have applied it to the supplier selection problem. In the next stage, a fuzzy programming technique, which is a common method used for solving multi-objective decision making (MODM) problems, is
considered. Finally, a numerical example is given to illustrate the modeling idea and this example is solved step-by-step.