Hybrid multi-criteria group decision-making for supplier selection problem with interval-valued Intuitionistic fuzzy data

The main objectives of supply chain management are reducing the risk of supply chain and production cost, increase the income, improve the customer services, optimizing the achievement level, and business processes which would increase ability, competency, customer satisfaction, and profitability. Further, the process of selecting the appropriate supplier capable of providing buyerchr('39')s requirements in terms of quality products with suitable price and at a suitable time and size is one of the most essential activities to create an efficient supply chain. Consequently, false decisions in the context of supplier selection would lead to negative effects. Usually, suitable supplier selection methods have been multi-criteria or attribute, so finding the optimal solution for supplier selection is demanding. The customary methods in this field have struggled with quantitative criteria however there are a wide range of qualitative criteria in supplier selection. this article has used interval valued intuitionistic fuzzy sets for selecting the appropriate suppliers, which reflect ambiguity and uncertainty far better than other methods. In this article, trapezoidal fuzzy membership function is used for lingual qualitative values. Goal programming satisfaction function (GPSF) is a kind of technique that helps decision makers in solving problems involving conflicting and competing criteria and objectives. Due to the importance of the issue, in this paper, hybrid approach with a group decision-making in Multiple Criteria Decision Making (MCDM) in the context of a range of interval-valued intuitionistic fuzzy sets is implemented to solve the supplier selection problem. In this model in phase 1, decision makers express their opinion about each alternative based on different attribute qualitatively, and after creating interval valued intuitionistic fuzzy membership, a new variable is defined that via its help, interval-valued intuitionistic fuzzy amounts are calculated for each alternative. because of Having capabilities and comprehensiveness in their inside, not only they are better than other fuzzy sets but also they are the best for tracing the real condition and environment in order to select suppliers. Thereafter, for each alternative upper and lower bonds are calculated based on interval-valued intuitionistic fuzzy amounts. In phase 2, Operator Weighted Average (OWA) algorithm is used to reach a collective consensus. After computing the degree of consensus, closeness coefficients is evaluated within the help of TOPSIS method, which is in fact one of the most practicable methods between multi-criteria decision-making methods, such as SAW, AHP, CP, VIKOR. With regard to closeness coefficient, the amount of closeness between individual and collective’s agreement is accounted. The main aim of this article is optimizing the closeness coefficient. The alternative with maximum closeness coefficient is closer to the ideal solution. The final goal of proposed model is ranking the suppliers, meaning that satisfy the main factors of decision making, which is why GPSF model is used. After giving goal and restrict functions, GPSF model will be solved and rank alternatives.