Supplier selection through interval type-2 trapezoidal fuzzy multi-attribute group decision-making method with logarithmic information measures

Supplier selection is a hot issue in logistics and procurement under the new economic situation. For the problems of supplier selection, the uncertainty and complexity of decision-making information often led to the mistakes in the process of group decision-making. In this paper, interval type-2 trapezoidal fuzzy (IT2TrF) information is used to deal with uncertainty and complex decision-making information, and a multi-attribute group decision making (MAGDM) method with IT2TrF information measures is designed for supplier selection problems. Specifically, we first present three axiomatic definitions for IT2TrF information measures. Then, based on logarithmic function, the IT2TrF logarithmic information entropy, the IT2TrF logarithmic similarity and the IT2TrF logarithmic cross-entropy are proposed to measure the fuzziness and similarity of decision-making information. In addition, an attribute weights determination method based on IT2TrF information entropy is established. Finally, a numerical example regarding assess the performance of suppliers is provided, and the comparative analysis demonstrates the applicability and feasibility of the developed MAGDM method.