Chapter 7 UTA METHODS

Abstract: UTA methods refer to the philosophy of assessing a set of value or utility functions, assuming the axiomatic basis of MAUT and adopting the preference disaggregation principle. UTA methodology uses linear programming techniques in order to optimally infer additive value/utility functions, so that these functions are as consistent as possible with the global decision-maker’s preferences (inference principle). The main objective of this chapter is to analytically present the UTA method and its variants and to summarize the progress made in this field. The historical background and the philosophy of the aggregation-disaggregation approach are firstly given in this chapter. The detailed presentation of the basic UTA algorithm is presented, including the discussion on the stability and sensitivity analyses. Several variants of the UTA method, which incorporate different forms of optimality criteria used in the LP formulation, are also discussed. The implementation of the UTA methods is illustrated by a general overview of UTA-based DSSs, as well as real-world decision-making applications. Finally, several potential future research developments of the UTA methodologies within the context of MCDA are discussed through this chapter