A GENERAL MULTILEVEL EVALUATION PROCESS FOR HYBRID MADM WITH UNCERTAINTY

Based on an evidential reasoning framework, a general multi-level evaluation process is developed in this paper for dealing with a multiple attribute decision making (MADM) problem with both quantitative and qualitative attributes. In this new process, a qualitative attribute may be evaluated by uncertain subjective judgments through multiple levels of factors and each of the judgments may be assigned by single or multiple experts in any rational way within the evidential reasoning framework. The qualitative attributes can then be quantified by means of general evaluation analysis and evidential reasoning. A few evaluation analysis models and the corresponding evidential reasoning algorithms are explored for parallel combination and hierarchical propagation of factor evaluations. With all the qualitative attributes being quantified by this rational process, the MADM problem represented by an extended decision matrix is then transformed into an ordinary decision matrix, which can be dealt with using a traditional MADM method. This new general evaluation process and the hybrid decision making procedure are demonstrated using a multiple attribute motor cycle evaluation problem with uncertainty.