An optimization approach to multiperson decision making based on different formats of preference information

Multiperson decision making (MPDM) problems with different formats of preference information are one of the emerging research areas in decision analysis. Existing approaches for dealing with different preference formats tend to be unwieldy. This paper proposes a new method to solve the problem, in which the preference information on alternatives provided by experts can be represented in four different formats, namely: 1) utility values; 2) preference orderings; 3) multiplicative preference relations; and 4) fuzzy preference relations. An optimization model is constructed to integrate the four formats of preference and to assess ranking values of alternatives. The model is shown to be theoretically sound and complete via a series of theorems, and then a corresponding algorithm is developed. A numerical example is given to illustrate the procedure. The proposed approach is more efficient and simpler than existing approaches because it does not need to unify different formats of preferences or to aggregate individual preferences into a collective one. Therefore, it overcomes a major shortcoming of existing approaches that lose or distort the original preference information in the process of unifying the formats