Using DEA for Evaluating the Attribute Weights and solving one MADM Problem

Multiple Attribute Decision Making (MADM) addresses the problem of choosing an optimum choice containing the highest degree of satisfaction from a set of alternatives which are characterized in terms of their attributes. In order to make a decision or choose a best alternative, a decision maker (DM) is often asked to provide his/her preferences either on alternatives or on the relative weights of attributes or on both of them. In this paper some basic principles from data envelopment analysis (DEA) is used in order to extract the necessary information for solving an MADM problem. We will introduce a comprehensive yet efficient approach for accountable and understandable MADM. For obtaining the attribute weights and choosing the best alternative, we use the Common Set of Weights (CSW) in DEA. The DMUs correspond to the alternatives which have to be evaluated. We will obtain the common set of weights of these DMUs and then we consider these weights as weight of attributes. We compute the efficiency score of each DMU and we will consider the efficient DMU as the best alternative