Abstract
In this paper, the approach to estimate a fuzzy weight vector from an interval comparison matrix is proposed. The interval comparison allows a decision maker to state his/her uncertain judgment as a range, instead of a crisp value. By increasing and decreasing its upper and lower bounds of the interval comparison by the inverse rates, the processed comparison matrices are derived from the given matrix. The membership function of the fuzzy weight is based on the certainty degrees of the interval weight vectors obtained from the processed matrices. The interval weight vector is defined as a closure of the normalized crisp weight vectors each of which is included in an interval comparison matrix. Its certainty degree is represented as the sum of the lower bounds of all the corresponding interval weights.
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