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Multi Criteria Decision Support System: Preference Information and Robustness

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New Contributions in Information Systems and Technologies

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 353))

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Abstract

The robustness analysis is a substantial and debatable issue in the multi-criteria decision support systems. The multi-criteria decision support systems always depend on preference information from a decision maker. Although it is evident that elicited preference information has a great impact on the result, research on the preference robustness in multi-criteria decision support system rather narrow in contrast to the well-established research robust decision making. This paper focuses on the multi-criteria decision support systems based on the multiple criteria sorting methods. The paper proposes an analyzing approach based on the concept of the preference robustness. The approach involved in the multi-criteria decision support system can provide valuable insight to a decision maker on how preferences influence the choice among alternatives. Moreover, the approach can be combined with other decision aiding methods as an additional technique for deriving a consensus when there are multiple preferences.

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Author information

Authors and Affiliations

  1. Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden

    Maria Kalinina

Authors
  1. Maria Kalinina
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Correspondence to Maria Kalinina .

Editor information

Editors and Affiliations

  1. DEI/FCT, Universidade de Coimbra, Coimbra, Portugal

    Alvaro Rocha

  2. Campus de Campolide, ISEGI, Lisboa, Portugal

    Ana Maria Correia

  3. DEIS, Università della Calabria, Arcavacata di Rende, Italy

    Sandra Costanzo

  4. DIS, Universidade do Minho, Guimarães, Portugal

    Luis Paulo Reis

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Kalinina, M. (2015). Multi Criteria Decision Support System: Preference Information and Robustness. In: Rocha, A., Correia, A., Costanzo, S., Reis, L. (eds) New Contributions in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 353. Springer, Cham. https://doi.org/10.1007/978-3-319-16486-1_63

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  • DOI: https://doi.org/10.1007/978-3-319-16486-1_63

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16485-4

  • Online ISBN: 978-3-319-16486-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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