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A New Method for Decision Making in the Intuitionistic Fuzzy Setting

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Artificial Intelligence and Soft Computing – ICAISC 2008 (ICAISC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5097))

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Abstract

The main problem of known methods for Multiple Criteria Decision Making in the Intuitionistic Fuzzy setting is that they are generally based on the intermediate type reduction. Such approaches lead inevitable to the loss of important information. Another problem is the choice of an appropriate method for the local criteria aggregation taking into account their ranks. The aim of this paper is to present a new method which makes it possible to solve the first problem and facilitates the solution of the second one. The method is based on the Dempster-Shafer Theory (DST). It allows to solve the Multiple Criteria Decision Making problem without intermediate type reduction for different approaches to aggregation of the local criteria. The usefulness of elaborated method is illustrated with known example of Multiple Criteria Decision Making problem.

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Authors and Affiliations

  1. Institute of Comp.& Information Sci., Technical University of Czestochowa, Dabrowskiego 73, 42-200, Czestochowa, Poland

    Ludmila Dymova, Izabela Róg & Pavel Sevastjanov

Authors
  1. Ludmila Dymova
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  2. Izabela Róg
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  3. Pavel Sevastjanov
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Leszek Rutkowski Ryszard Tadeusiewicz Lotfi A. Zadeh Jacek M. Zurada

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© 2008 Springer-Verlag Berlin Heidelberg

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Dymova, L., Róg, I., Sevastjanov, P. (2008). A New Method for Decision Making in the Intuitionistic Fuzzy Setting. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_23

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  • DOI: https://doi.org/10.1007/978-3-540-69731-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69572-1

  • Online ISBN: 978-3-540-69731-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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