A Statistical Approach to Complex Multi-Criteria Decisions, in, D. Ruan (Ed.) Computational Intelligence in Complex Decision Systems, Chapter 6

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Complex decisions problems have most of the time multiple-criteria dimensions. Many existing multiple-criteria decision tools are however plagued with difficulties due to uncertainties on data and preference weights, multiple decision-makers, correlations between criteria, etc., and last but not least, undesirable properties, like rank reversal. The chapter investigates an original approach using the correlations between criteria, as a measure of distance between ranking solutions. Geometrical interpretations are given for two and three-dimensional problems. It is shown how the proposed framework, which is valid for any dimension, addresses uncertainties, and how it enhances the rank-reversal immunity. This methodology serves two objectives: firstly, it provides a statistical tool for interpreting decision-making processes for large samples of customers, or clients on markets; secondly, it provides a support for multiple-criteria ranking of alternatives in the presence of uncertainties. The on-going development of the approach, and several future research directions are also indicated.
Original languageEnglish
Title of host publicationAtlantis Computational Intelligence Systems
EditorsDa Ruan
PublisherAtlantis Press
Pages149-184
Number of pages36
Volume2
ISBN (Print)978-90-78677-27-7
Publication statusPublished - 1 Jun 2010

Bibliographical note

Da Ruan

Keywords

  • Multi-Criteria Analysis
  • ranks and scores
  • correlations

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