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International Conference on Computational Collective Intelligence

ICCCI 2014: Computational Collective Intelligence. Technologies and Applications pp 454–465Cite as

The Selection of Multicriteria Method Based on Unstructured Decision Problem Description

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8733))

Abstract

Decision support processes and methods require applying numerous mathematical transformations, including one of the developed processes of multicriteria analysis. The core of most existing processes is usually one of the multicriteria decision aid methods (MCDA). The paper presents research focused on identifying which factors of a decision situation are significant for selecting a multicriteria method. The identified factors were analyzed with data-mining methods. Conclusions contain an outline of factors of decision situations that support MCDA methods to support decisions in particular situations.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology Szczecin, Poland

    Jarosław Wątróbski, Jarosław Jankowski & Zbigniew Piotrowski

Authors
  1. Jarosław Wątróbski
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  2. Jarosław Jankowski
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  3. Zbigniew Piotrowski
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Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Yeungnam University, Korea

    Dosam Hwang  & Jason J. Jung  & 

  2. Institute of Informatics, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc-Thanh Nguyen

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© 2014 Springer International Publishing Switzerland

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Wątróbski, J., Jankowski, J., Piotrowski, Z. (2014). The Selection of Multicriteria Method Based on Unstructured Decision Problem Description. In: Hwang, D., Jung, J.J., Nguyen, NT. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2014. Lecture Notes in Computer Science(), vol 8733. Springer, Cham. https://doi.org/10.1007/978-3-319-11289-3_46

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  • DOI: https://doi.org/10.1007/978-3-319-11289-3_46

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11288-6

  • Online ISBN: 978-3-319-11289-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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