دانلود مقاله ISI انگلیسی شماره 81591
ترجمه فارسی عنوان مقاله

یک روش برنامه ریزی خطی فازی شهودی برای انتخاب برون سپاری ارائه دهنده تدارکات

عنوان انگلیسی
An intuitionistic fuzzy linear programming method for logistics outsourcing provider selection
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
81591 2015 15 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Knowledge-Based Systems, Volume 82, July 2015, Pages 80–94

ترجمه کلمات کلیدی
رابطه اولویت فازی شهودی؛ برنامه ریزی خطی فازی شهودی؛ ارائه دهنده برون سپاری لجستیک؛ تصمیم گیری گروه؛ TOPSIS (روش برای اولویت سفارش با شباهت به راه حل ایده آل)
کلمات کلیدی انگلیسی
Intuitionistic fuzzy preference relation; Intuitionistic fuzzy linear programming; Logistics outsourcing provider; Group decision making; TOPSIS (technique for order preference by similarity to ideal solution)

چکیده انگلیسی

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.