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Ranking Decision Variants by Subjective Paired Comparisons in Cases with Incomplete Data

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Computational Science and Its Applications — ICCSA 2003 (ICCSA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2669))

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Abstract

The pairwise comparison method is widely used to rank a finite, usually small number of decision variants especially in a case when neither a direct evaluation nor the utility theory gives satisfactory results. In this method, an expert or a group of experts is asked to provide his/their opinions concerning each pair of factors expressing a relative importance of one variant in a pair over the second one. It happens however that an expert or few experts cannot provide his/their opinions concerning a pair or pairs of factors. In such a case the resulting judgement matrices are incomplete and a problem of estimating missing data arises. The paper addresses some issues concerning lacking data. Some numerical examples are included.

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Author information

Authors and Affiliations

  1. Faculty of Electrical and Control Engineering, Technical University of Gdansk, Narutowicza 11/12, Gdansk, POLAND, 80-952

    Miroslaw Kwiesielewicz

  2. Faculty of Electrical and Control Engineering, Technical University of Gdansk, Narutowicza 11/12, Gdansk, POLAND, 80-952

    Ewa van Uden

Authors
  1. Miroslaw Kwiesielewicz
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  2. Ewa van Uden
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Editor information

Editors and Affiliations

  1. Army High Performance Computing Research Center, USA University of Minessota Department of Computer Science and Engineering, MN, 55455, USA

    Vipin Kumar

  2. Department of Computer Science, University of Calgary, Calgary, AB, T2N1N4, Canada

    Marina L. Gavrilova

  3. Heuchera Technologies Inc., 122 9251-8Yonge Street, Richmond Hill, ON, Canada, L4C 9T3

    Chih Jeng Kenneth Tan

  4. School of Computer Science, The Queen’s University of Belfast, Belfast, BT7 1NN, Northern Ireland UK

    Chih Jeng Kenneth Tan

  5. Département d’informatique et de recherche opérationelle Montréal, Université de Montréal, Québec, H3C 3J7, Canada

    Pierre L’Ecuyer

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© 2003 Springer-Verlag Berlin Heidelberg

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Kwiesielewicz, M., van Uden, E. (2003). Ranking Decision Variants by Subjective Paired Comparisons in Cases with Incomplete Data. In: Kumar, V., Gavrilova, M.L., Tan, C.J.K., L’Ecuyer, P. (eds) Computational Science and Its Applications — ICCSA 2003. ICCSA 2003. Lecture Notes in Computer Science, vol 2669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44842-X_22

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  • DOI: https://doi.org/10.1007/3-540-44842-X_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40156-8

  • Online ISBN: 978-3-540-44842-6

  • eBook Packages: Springer Book Archive

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