BW-MaxEnt: A Novel MCDM Method for Limited Knowledge

With the development of social economy and an enlarged volume information, application multiple-criteria decision making (MCDM) has become increasingly wide deep. As a brilliant MCDM technique, best–worst method (BWM) attracted many scholars’ attention because it can determine weights criteria with less comparison time higher consistency between judgments than analytic hierarchy process. However, effectiveness BWM is based on complete information among criteria. Considering fact that makers may have limited energy to study all criteria, they cannot construct system. In this paper, we propose novel named BW-MaxEnt combines maximum entropy (MaxEnt) identify unfamiliar incomplete information. The model be translated into convex optimization problem solved effectively overall optimal solution. Finally, practical concerning procurement GPU workstations illustrates feasibility proposed method.