Hesitant analytic hierarchy process

Bin Zhu, Zeshui Xu, Ren Zhang and Mei Hong

European Journal of Operational Research, 2016, vol. 250, issue 2, 602-614

Abstract: In traditional analytic hierarch process (AHP), decision makers (DMs) are required to provide crisp judgments over paired comparisons of objectives to construct comparison matrices. To enhance the modeling ability of traditional AHP, we propose hesitant AHP (H-AHP) that can consider the hesitancy experienced by the DMs in decision. H-AHP is characterized by hesitant judgments, where each hesitant judgment can be represented by several possible values. Different probability distributions can be used to further describe hesitant judgments according to the DMs’ preferences. Based on a hesitant comparison matrix (HCM) that consists of hesitant judgments, we define two indices to measure the consistency degree and the consensus degree of the HCM respectively. From a stochastic point of view, a new prioritization method is developed to derive priorities from HCMs, where the results are with probability interpretations. We provide a step by step procedure for H-AHP, and demonstrate this new method with a real-life decision making problem.

Keywords: Uncertainty modeling; Decision support systems; Comparison matrix; Simulation methodology (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:250:y:2016:i:2:p:602-614

DOI: 10.1016/j.ejor.2015.09.063

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