4.7 Article

A new multiplicative consistency based method for decision making with triangular fuzzy reciprocal preference relations

Journal

FUZZY SETS AND SYSTEMS
Volume 315, Issue -, Pages 1-25

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.fss.2016.12.010

Keywords

Decision analysis; TFRPR; Quasi TFRPR; Consistency analysis; Programming model

Funding

  1. State Key Program of National Natural Science of China [71431006]
  2. Projects of Major International Cooperation NSFC [71210003]
  3. National Natural Science Foundation of China [71571192, 71501189, 71201089, 71271217]
  4. Postdoctoral Science Special Foundation of China [2015T80901]
  5. Innovation-Driven Planning Foundation of Central South University [2016CXS027]
  6. Hunan Province Foundation for Distinguished Young Scholars of China [20163-J1024]

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Triangular fuzzy reciprocal preference relations (TFRPRs) are good choices to denote the decision makers' fuzzy preferences. Consistency analysis is a very important topic to preference relations that can avoid the illogical ranking order. However, all previous multiplicative consistency concepts for TFRPRs cannot well address this type of preference relations. To address this issue, this paper introduces a new multiplicative consistency concept for TFRPRs, which can be seen as a natural extension of Tanino's multiplicative consistency concept for reciprocal preference relations. Based on the new consistency concept, 0-1 mixed' programming models for judging the multiplicative consistency of TFRPRs are constructed, and an approach for deriving multiplicative consistent TFRPRs is provided. Considering the incomplete case, programming models to determine missing values ate constructed. Subsequently, a multiplicative consistency based method for decision making with TFRPRs is presented that can address the inconsistent and incomplete cases. Meanwhile, illustrative examples are provided to show the concrete application of the proposed procedure, and comparison analysis is also made. (C) 2016 Elsevier B.V. All rights reserved.

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