An intuitionistic fuzzy linear programming method for logistics outsourcing provider selection
In order to reduce costs and enhance their core competitiveness, many companies tend to choose the logistics outsourcing. The selection of logistics outsourcing provider plays an important role for the success of outsourcing. In this paper, we formulate the logistics outsourcing provider selection as a kind of group decision making (GDM) problems with intuitionistic fuzzy preference relations (IFPRs). A new intuitionistic fuzzy linear programming method is proposed for solving such problems. First, we construct an intuitionistic fuzzy linear programming model to derive priority weights from IFPRs. Depended on the construction of non-membership functions, this intuitionistic fuzzy linear programming model is solved by the developed three kinds of approaches including the optimistic, pessimistic and mixed approaches. Then by the idea of TOPSIS (technique for order preference by similarity to ideal solution), the experts weights are determined objectively. Combining the experts weights with the derived priority weights, the corresponding method for GDM with IFPRs is presented. An example of logistics outsourcing provider selection is provided to illustrate the proposed method. Finally, the intuitionistic fuzzy programming method is further generalized to the case of more general membership and non-membership functions.
intuitionistic fuzzy linear programming logistics outsourcing provider group decision making intuitionistic fuzzy preference relation topsis (technique for order preference by similarity to ideal solution)