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Constrained consistency enforcement in AHP

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  • Benítez, Julio
  • Carpitella, Silvia
  • Certa, Antonella
  • Izquierdo, Joaquín

Abstract

Decision-making in the presence of intangible elements must be based on a robust, but subtle, balance between expert know-how and judgment consistency when eliciting that know-how. This balance is frequently achieved as a trade-off reached after a feedback process softens the tension frequently found between one force steadily pulling towards (full) consistency, and another force driven by expert feeling and opinion. The linearization method, developed by the authors in the framework of the analytic hierarchy process, is a pull-towards-consistency mechanism that shows the path from an inconsistent body of judgment elicited from an expert towards consistency, by suggesting optimal changes to the expert opinions. However, experts may be reluctant to alter some of their issued opinions, and may wish to impose constraints on the adjustments suggested by the consistency-enforcement mechanism. In this paper, using the classical Riesz representation theorem, the linearization method is accommodated to consider various types of constraints imposed by experts during the abovementioned feedback process.

Suggested Citation

  • Benítez, Julio & Carpitella, Silvia & Certa, Antonella & Izquierdo, Joaquín, 2020. "Constrained consistency enforcement in AHP," Applied Mathematics and Computation, Elsevier, vol. 380(C).
    • Handle: RePEc:eee:apmaco:v:380:y:2020:i:c:s0096300320302423
    DOI: 10.1016/j.amc.2020.125273
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    References listed on IDEAS

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    1. Saaty, Thomas L., 2003. "Decision-making with the AHP: Why is the principal eigenvector necessary," European Journal of Operational Research, Elsevier, vol. 145(1), pages 85-91, February.
    2. Huang, Jing & Boland, John & Liu, Weidong & Xu, Chang & Zang, Haixiang, 2018. "A decision-making tool for determination of storage capacity in grid-connected PV systems," Renewable Energy, Elsevier, vol. 128(PA), pages 299-304.
    3. Ishizaka, Alessio & Siraj, Sajid, 2018. "Are multi-criteria decision-making tools useful? An experimental comparative study of three methods," European Journal of Operational Research, Elsevier, vol. 264(2), pages 462-471.
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