An evidential reasoning approach for multiple-attribute decision making with uncertainty

Abstract

A new evidential reasoning based approach is proposed that may be used to deal with uncertain decision knowledge in multiple-attribute decision making (MADM) problems with both quantitative and qualitative attributes. This approach is based on an evaluation analysis model and the evidence combination rule of the Dempster-Shafer theory. It is akin to a preference modeling approach, comprising an evidential reasoning framework for evaluation and quantification of qualitative attributes. Two operational algorithms have been developed within this approach for combining multiple uncertain subjective judgments. Based on this approach and a traditional MADM method, a decision making procedure is proposed to rank alternatives in MADM problems with uncertainty. A numerical example is discussed to demonstrate the implementation of the proposed approach. A multiple-attribute motor cycle evaluation problem is then presented to illustrate the hybrid decision making procedure.>