Displaying similar documents to “On Solving Stochastic MADM Problems”

A model of decision with linguistic knowledge.

María Teresa Lamata Jiménez (1994)

Mathware and Soft Computing

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The aim of this paper is to develop a new aggregating method for the decision problem in which the possible values of rewards are known in linguistic terms. We show new operators for solving this problem, as well as the way in which OWA operators provide us with an adequate framework for representing the optimism degree of the decision maker in case we have no information about the real state.

Extension of stochastic dominance theory to random variables

Chi-Kwong Li, Wing-Keung Wong (2010)

RAIRO - Operations Research

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In this paper, we develop some stochastic dominance theorems for the location and scale family and linear combinations of random variables and for risk lovers as well as risk averters that extend results in Hadar and Russell (1971) and Tesfatsion (1976). The results are discussed and applied to decision-making.