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Weak and Strong Consistency of an Interval Comparison Matrix

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12482))

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Abstract

We consider interval-valued pairwise comparison matrices and two types of consistency – weak (consistency for at least one realization) and strong (acceptable consistency for all realizations). Regarding weak consistency, we comment on the paper [Y. Dong and E. Herrera-Viedma, Consistency-Driven Automatic Methodology to Set Interval Numerical Scales of 2-Tuple Linguistic Term Sets and Its Use in the Linguistic GDM With Preference Relation, IEEE Trans. Cybern., 45(4):780–792, 2015], where, among other results, a characterization of weak consistency was proposed. We show by a counterexample that in general the presented condition is not sufficient for weak consistency. It provides a full characterization only for matrices up to size of three. We also show that the problem of having a closed form expression for weak consistency is closely related with P-completeness theory and that an optimization version of the problem is indeed P-complete. Regarding strong consistency, we present a sufficient condition and a necessary condition, supplemented by a small numerical study on their efficiency. We leave a complete characterization as an open problem.

With a correction on paper DOI 10.1109/TCYB.2014.2336808.

Supported by the Czech Science Foundation Grant P403-18-04735S.

The counterexample and the correction provided by this paper were originally submitted to IEEE Trans. Cybern. as a technical note, but the journal editors resigned to accept this note which points to incorrect statements published there.

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Notes

  1. 1.

    Sometimes the notion of “acceptable consistency” is used, but due to ambiguity we do not use it in this sense.

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Correspondence to Milan Hladík .

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Hladík, M., Černý, M. (2020). Weak and Strong Consistency of an Interval Comparison Matrix. In: Huynh, VN., Entani, T., Jeenanunta, C., Inuiguchi, M., Yenradee, P. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2020. Lecture Notes in Computer Science(), vol 12482. Springer, Cham. https://doi.org/10.1007/978-3-030-62509-2_2

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  • DOI: https://doi.org/10.1007/978-3-030-62509-2_2

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