5. Interval MADM with Unknown Weight Information

Excerpt

There has been little research on interval MADM with unknown weight information up to now. Based on the deviation degrees of interval numbers and the idea of maximizing deviations of attributes, in this chapter, we first introduce a simple and straightforward formula, and in the situations where the decision maker has no preferences on alternatives, we introduce a MADM method based on possibility degrees and deviation degrees of interval numbers. Then for the situations where the decision maker has preferences on alternatives, we introduce a MADM method which can not only sufficiently consider the priori fuzzy information of normalization evaluations, but also meet the decision maker’s subjective requirements as much as possible. Finally, we introduce a ranking method for alternatives based on the UOWA operator, and establish a consensus maximization model for determining attribute weights in uncertain MAGDM. In order to make the readers easy to understand and master the methods, we illustrate them with some practical examples. …