Assessment aggregation in the evidential reasoning approach to MADM under uncertainty: Orthogonal versus weighted sum

Abstract

In this paper, we revisit the evidential reasoning (ER) approach to multiple-attribute decision making (MADM) with uncertainty. The attribute aggregation problem in MADM under uncertainty is generally formulated as a problem of evidence combination. Then several new aggregation schemes are proposed and simultaneously their theoretical features are explored. A numerical example traditionally examined in published sources on the ER approach is used to illustrate the proposed techniques. © Springer-Verlag Berlin Heidelberg 2004.