A New Entropy-Based Approach to Determine the Weights of Decision Makers for Each Criterion With Crisp and Interval Data in Group Decision Making Under Multiple Attribute

Abstract

The aim of this article is to develop a modified version of the original entropy approach to determine weights of decision makers (DMs) in multi-attribute group decision making (MAGDM) contexts with both crisp and interval data, in which the weights of experts (or DMs) are derived from the decision matrices and DMs have different weights for different criteria. In the proposed method, the experts' weight for each criterion depends on the uncertainty measure of DMs comparisons. In other words, the DMs who give less uncertainty judgments (or less entropy measures), will be evaluated as more importance, and vice-versa. Finally, a numerical example is given to demonstrate the feasibility of the developed method.