a hybrid dhfea/ahp method for ranking units with hesitant fuzzy data

One of the attractive subjects in decision analysis is the investigating of the uncertain data which is inevitable in many real-world applications. fuzzy sets theory has been introduced to investigate the uncertain data which formulates the uncertainty by using the membership functions. however, in many real world applications, it is difficult to determine the exact amount of the membership value and so the skepticism can be raised during the decision-making process. the new perspective manages the uncertainty caused by the skepticism and in this case, the most important issues are to collect the hesitant fuzzy information and to select the optimal alternative. this study develops the deviation-oriented hesitant fuzzy envelopment analysis (dhfea) based on deviation values. the hybrid fuzzy dhfea/ahp approach derives the ahp pair-wise comparisons by hesitant fuzzy dea and utilizes ahp to fully rank units. it shows that the proposed approach generates a logical ranking of units that has perfect compatibility withhesitant fuzzy dea ranking and there is no any form of subjective analysis engaged within the methodology. the potential application of theproposed method is illustrated with a numerical example.