4.7 Article

And-like-uninorm-based transitivity and analytic hierarchy process with interval-valued fuzzy preference relations

Journal

INFORMATION SCIENCES
Volume 539, Issue -, Pages 375-396

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2020.05.052

Keywords

Analytic hierarchy process; Multi-criteria decision making; Interval-valued fuzzy preference relations; Multiplicative transitivity; Acceptability; And-like-uninorm

Funding

  1. National Natural Science Foundation of China [71671160]
  2. Zhejiang Provincial Natural Science Foundation of China [LY19G010004]
  3. Humanities and Social Science Foundation of Ministry of Education of China [18YJA880076]

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The framework of interval-valued fuzzy preference relations (IVFPRs) is adequate and effective to model human preference evaluations under indeterminacy. This paper analyzes three recently presented multiplicative transitivity models of IVFPRs and exposes their drawbacks. An and-like-uninorm-based functional transitivity equation is developed to introduce a multiplicative consistency notion for IVFPRs. Based on the transitivity logarithmic equation, a geometric-consistency index is further proposed to compute the inconsistency level of an IVFPR. The paper builds a logarithmic least squares model with row indeterminacy constraints and equivalently transforms it into a quadratic programming model for finding a closed-form solution of the normalized interval-valued fuzzy weights of IVFPRs. A novel method is subsequently presented to check the acceptability of an IVFPR by examining its acceptable consistency and acceptable indeterminacy. An approach including an and-like-uninorm-based maximization model is introduced to aggregate local interval-valued fuzzy weights and an interval fuzzy analytic hierarchy process is designed step-by-step. An illustrative example and a comparison study are utilized to demonstrate the performance and merits of the presented models. Meanwhile, an outstanding undergraduate student selection problem in international exchange is provided to show the application of the proposed decision method. (C) 2020 Elsevier Inc. All rights reserved.

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