Robust multi-criteria ranking with additive value models and holistic pair-wise preference statements

M Kadzinski, TP Tervonen

Research output: Contribution to journalArticleAcademicpeer-review

85 Citations (Scopus)

Abstract

We consider a problem of ranking alternatives based on their deterministic performance evaluations on multiple criteria. We apply additive value theory and assume the Decision Maker¿s (DM) preferences to be representable with general additive monotone value functions. The DM provides indirect preference information in form of pair-wise comparisons of reference alternatives, and we use this to derive the set of compatible value functions. Then, this set is analyzed to describe (1) the possible and necessary preference relations, (2) probabilities of the possible relations, (3) ranges of ranks the alternatives may obtain, and (4) the distributions of these ranks. Our work combines previous results from Robust Ordinal Regression, Extreme Ranking Analysis and Stochastic Multicriteria Acceptability Analysis under a unified decision support framework. We show how the four different results complement each other, discuss extensions of the main proposal, and demonstrate practical use of the approach by considering a problem of ranking 20 European countries in terms of 4 criteria reflecting the quality of their universities.
Original languageEnglish
Pages (from-to)169-180
Number of pages12
JournalEuropean Journal of Operational Research
Volume228
Issue number1
DOIs
Publication statusPublished - 2013

Research programs

  • EUR ESE 32

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