WAGE: Weighting with AHP, Grey Numbers, and Entropy for Multiple-Criteria Group Decision Making Problem

Now, the use of smart mobile devices in social environment is popular since the paradigm of ubiquitous computing has emerged. Here the multiple-criteria group decision making (MCDM) problem occasionally occurs due to frequent interactions among many people. The classical MCDM solutions need improvement to be applied to real-world decision problems where subjectivity and vagueness are required to be handled in determining the weights of the criteria. This paper extends the classical MCDM solution, the technique ordered preference by similarity to the ideal solution (TOPSIS), by employing analytic hierarchy process (AHP), grey theory, and the concept of entropy. The effectiveness of the proposed scheme is demonstrated with a case study.