Multi-criteria decision making: The case of large and distinct decision makers

This paper considers a multi-criteria decision making (MCDM) problem where a set of alternatives are to be evaluated or ranked. However, unlike in a traditional MCDM approach, each alternative is evaluated by a distinct group of decision makers who are different from those evaluating the other competing alternatives. In addition, the decision makers for each alternative are large (in hundreds and above). We propose a sampling based modeling technique to transform this special type of MCDM problem into a traditional MCDM format. Following this, the sampling distributions of the ranks of the alternatives are displayed with Boxplot to aid decision making. A numerical example showing the effectiveness of the proposed approach is presented.