Most of the evaluation problems are comprehensive and with ever-increasingly more uncertainties. By quantifying the involved uncertainties, Basic Uncertain Information can both well handle and merge those uncertainties in the input information. This study proposed a two-level comprehensive evaluation model by using some merging techniques which can consider both the original preference information and the bi-polar preference over the information with high certainty degrees. A numerical application in educational evaluation is also proposed to verify the effectiveness and flexibility of the proposed model.

This study firstly proposes a simpler method for evaluating one certain object’s quality with multiple criteria according to some preset evaluation threshold values that are real numbers. In real life, numerous individual valuations are provided with distributional linguistic input information and with multiple criteria, and thus they can become heterogeneous. Against this background, by using OWA weight functions we propose an extended setting and some methods to generate distributional evaluation threshold values which are suitable for the corresponding thresholds-based evaluation method. Some special definitions and formulations are also well provided with necessary analyses and comments. A numerical example of reservoir evaluation and effect are also illustrated.