Abstract

Uncertainties are pervasive in ever-increasing more practical evaluation and decision making environments. Numerical information with uncertainty losses more or less credibility, which makes it possible to use bi-polar preference based weights allocation method to attach differing importance to different information granules in evaluation. However, there lacks effective methodologies and techniques to simultaneously consider various categories of involved bi-polar preferences, not merely the magnitude of main data which ordered weighted averaging aggregation can well handle. This work proposes some types and categories of bi-polar preference possibly involved in preference and uncertain evaluation environment, discusses some methods and techniques to elicit the preference strengths from practical backgrounds, and suggests several techniques to generate corresponding weight vectors for performing bi-polar preference based information fusion. Detailed decision making procedure and numerical example with management background are also presented. This work also presents some practical approaches to apply preferences and uncertainties involved aggregation techniques in decision making.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call