A statistical multi-criteria procedure with stochastic preferences

P.L. Kunsch

International Journal of Multicriteria Decision Making, 2010, vol. 1, issue 1, 49-73

Abstract: This article presents a simple and robust multi-criteria procedure providing the set of compromise rankings of alternatives, for one or many decision-makers, given some preference relationships between the criteria. The procedure is derived from the properties of the set of rank, or score vectors of the alternatives. The Pearson correlation serves as a measure of distance between two such vectors. The identification of all possible compromise rank vectors is made by a Monte Carlo analysis, using random weights. The probabilities of alternatives occupying the ranks are provided. The procedure is immune against rank reversals.

Keywords: multicriteria decision making; MCDM; statistical procedures; stochastic preferences; rank reversals; correlation distance; rank vectors; score vectors; compromise rank vectors; preference relationships; random weights; rank matrix; maximum number of criteria. (search for similar items in EconPapers)
Date: 2010
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