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International Conference on Algorithmic Decision Theory

ADT 2009: Algorithmic Decision Theory pp 168–179Cite as

A Prescriptive Approach for Eliciting Imprecise Weight Statements in an MCDA Process

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5783))

Abstract

In this article, we discuss decision making involving multiple objectives (MCDA) and especially the lack of more prescriptively useful elicitation methods for weights within MCDA. We highlight the discrepancy between how elicitation is handled in current decision analysis applications and the abilities of real decision-makers to provide what is required from them. Based on theory and highlighted problems with current methods, we propose a novel approach for weight elicitation which relaxes the need for numeric preciseness from decision-makers and reduces some of the practical issues related to such processes. The method is tested in a comparative study, as well as employed in a real-life case study.

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Author information

Authors and Affiliations

  1. Dept. of Computer and Systems Sciences, Stockholm University and, Royal Institute of Technology, Forum 100, SE-164 40, Kista, Sweden

    Mona Riabacke, Mats Danielson, Love Ekenberg & Aron Larsson

  2. Dept. of Information Technology and Media, Mid Sweden University, SE-851 70, Sundsvall, Sweden

    Aron Larsson

Authors
  1. Mona Riabacke
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  2. Mats Danielson
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  3. Love Ekenberg
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  4. Aron Larsson
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Editor information

Editors and Affiliations

  1. Department of Pure and Applied Mathematics, University of Padova, Via Trieste 63, 35121, Padova, Italy

    Francesca Rossi

  2. LAMSADE-CNRS, University of Paris Dauphine, Place du Maréchal De Lattre de Tassigny, 75775, Paris Cedex 16, France

    Alexis Tsoukias

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© 2009 Springer-Verlag Berlin Heidelberg

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Riabacke, M., Danielson, M., Ekenberg, L., Larsson, A. (2009). A Prescriptive Approach for Eliciting Imprecise Weight Statements in an MCDA Process. In: Rossi, F., Tsoukias, A. (eds) Algorithmic Decision Theory. ADT 2009. Lecture Notes in Computer Science(), vol 5783. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04428-1_15

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  • DOI: https://doi.org/10.1007/978-3-642-04428-1_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04427-4

  • Online ISBN: 978-3-642-04428-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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