Abstract
Ahstract-A decision making model is proposed within the framework of the Analytic Hierarchy Process (AHP), when the opinions of decision makers are expressed as incomplete interval additive reciprocal preference relations due to the complexity and uncertainty of real-world environments. Based on the new concept of additive approximation-consistency, a goal programming model is constructed to estimate the missing information in incomplete interval additive reciprocal comparison matrices. It is found that when the permutation of alternatives is different, the estimated preference information may be different. Then the average values of the obtained preference information are used to complement incomplete interval additive reciprocal comparison matrices. A new algorithm is proposed to address the decision making problem with incomplete interval additive reciprocal preference relations. The proposed method and algorithm are illustrated by carrying out numerical results.
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