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Educing Inconsistency In Fuzzy Ahp By Mathematical Programming Models

Author

Listed:
  • MEHDI GHAZANFARI

    (Iran University of Science & Technology, Tehran, Iran)

  • MAJID NOJAVAN

    (Faculty of Engineering, Islamic Azad University, South Branch, Tehran, Iran)

Abstract

The inconsistency of judgments in the fuzzy Analytic Hierarchy Process (AHP) is a crucial issue. To make the appropriate decision, the inconsistency in decision maker's (DM) judgments needs to be eliminated or reduced. This paper proposes two mathematical models to deal with inconsistency in fuzzy AHP. In the first model, the DM's judgments are modified where the preference order of the DM's judgments remained unchanged. The second model allows reversing the preference orders of judgments. The proposed models aim to eliminate or reduce the inconsistency of fuzzy AHP by changing judgments. The models cause fewer changes for the high certain judgments. Two examples solved by the proposed models are included for purposes of illustration.

Suggested Citation

  • Mehdi Ghazanfari & Majid Nojavan, 2004. "Educing Inconsistency In Fuzzy Ahp By Mathematical Programming Models," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 21(03), pages 379-391.
    • Handle: RePEc:wsi:apjorx:v:21:y:2004:i:03:n:s0217595904000291
    DOI: 10.1142/S0217595904000291
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    Citations

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    Cited by:

    1. Kun Chen & Gang Kou & J. Michael Tarn & Yan Song, 2015. "Bridging the gap between missing and inconsistent values in eliciting preference from pairwise comparison matrices," Annals of Operations Research, Springer, vol. 235(1), pages 155-175, December.
    2. Valdecy Pereira & Helder Costa, 2015. "Nonlinear programming applied to the reduction of inconsistency in the AHP method," Annals of Operations Research, Springer, vol. 229(1), pages 635-655, June.

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