Rough approximation of a preference relation for stochastic multi-attribute decision problems

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Abstract

Multi-attribute decision problems where the performances of the alternatives are random variables are considered in this paper. The suggested approach grades the probabilities of preference of one alternative over another with respect to the same attribute. Based on the graded probabilistic dominance relation, the pairwise comparison information table is defined. The global preferences of the decision maker can be seen as a rough binary relation. The present paper proposes to approximate this preference relation by means of the graded probabilistic dominance relation with respect to the subsets of attributes. © Springer-Verlag Berlin Heidelberg 2005.

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Yue, C., Yao, S., Zhang, P., & Cui, W. (2006). Rough approximation of a preference relation for stochastic multi-attribute decision problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3613 LNAI, pp. 1242–1245). Springer Verlag. https://doi.org/10.1007/11539506_155

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