Abstract
Even if the given data are crisp, there exists uncertainty in decision making process and inconsistency based on human judgements. The purpose of this paper is to obtain the evaluations which reflect such an uncertainty and inconsistency of the given information. Based on the idea that intervals are more suitable than crisp values to represent evaluations in uncertain situations, we introduce this interval analysis concept into two well-known decision making models, DEA and AHP. In the conventional DEA, the relative efficiency values are measured and in the proposed interval DEA, the efficiency values are defined as intervals considering various viewpoints of evaluations. In the conventional AHP, the priority weights of alternatives are obtained and in the proposed interval AHP, the priority weights are also defined as intervals reflecting the inconsistency among the given judgements.
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Entani, T., Sugihara, K., Tanaka, H. (2006). Interval Evaluations in DEA and AHP. In: Kahraman, C. (eds) Fuzzy Applications in Industrial Engineering. Studies in Fuzziness and Soft Computing, vol 201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33517-X_11
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DOI: https://doi.org/10.1007/3-540-33517-X_11
Publisher Name: Springer, Berlin, Heidelberg
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