Abstract
The interval Analytic Hierarchy Process (AHP) has been proposed to express vague evaluations of the decision maker as a normalized interval weight vector. In this paper, we apply the evidence theory to the representation of the vague evaluations as an alternative way. Accordingly, in the proposed approach, a basic probability assignment (BPA) is used for representing vague priority weights instead of a normalized interval weight vector. We formulate the problem estimating a BPA from a given pairwise comparison matrix as a linear programming problem. We investigate the relation between the proposed approach and the interval AHP. We show that the formulated BPA estimation problem is equivalent to the problem of estimating a normalized interval weight vector with an additional constraint.
This work was partially supported by JSPS KAKENHI Grant Number 17K18952.
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Inuiguchi, M. (2018). An Evidence Theoretic Approach to Interval Analytic Hierarchy Process. In: Huynh, VN., Inuiguchi, M., Tran, D., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2018. Lecture Notes in Computer Science(), vol 10758. Springer, Cham. https://doi.org/10.1007/978-3-319-75429-1_6
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DOI: https://doi.org/10.1007/978-3-319-75429-1_6
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