Journal
KNOWLEDGE-BASED SYSTEMS
Volume 127, Issue -, Pages 1-15Publisher
ELSEVIER
DOI: 10.1016/j.knosys.2017.03.010
Keywords
Group decision making; Hesitant fuzzy preference relation; Multiplicative consistency; Consensus; Distance measure
Categories
Funding
- State Key Program of National Natural Science of China [71431006]
- National Natural Science Foundation of China [71571192, 71501189]
- Natural Science Foundation of Hunan Province [2017JJ3397]
- Hunan Province Foundation for Distinguished Young Scholars of China [2016JJ1024]
- Innovation-Driven Planning Foundation of Central South University [2015CX010, 2016CXS027]
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This paper focuses on group decision making with hesitant fuzzy preference relations (HFPRs). To derive the consistent ranking order, a new multiplicative consistency concept for HFPRs is introduced that considers all information offered by the decision makers. The main feature is that this concept neither adds values to hesitant fuzzy elements nor disregards any information provided by the decision makers. To judge the multiplicative consistency of HFPRs, 0-1 mixed programming models are constructed. According to the assumption that there is an independent uniform distribution on values in hesitant fuzzy elements, the hesitant fuzzy priority weight vector is derived from multiplicative consistent reciprocal preference relations and their probabilities. Meanwhile, several consistency based 0-1 mixed models to estimate missing values in incomplete HFPRs are constructed that can address the situation where ignored objects exist. Considering the consensus in group decision making, a distance measure based consensus index is defined, and a method for improving the group consensus is provided to address the situation where the consensus requirement is unsatisfied. Then, a distance measure between any two HFPRs is introduced that is used to define the weights of the decision makers. Furthermore, a multiplicative consistency and consensus based interactive algorithm for group decision making with HFPRs is developed. Finally, a multi-criteria group decision making problem with HFPRs is offered to show the concrete application of the procedure, and comparison analysis is also made. (C) 2017 Elsevier B.V. All rights reserved.
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