Journal
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
Volume 65, Issue -, Pages 28-40Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.omega.2015.12.005
Keywords
Group decision making; Hesitant fuzzy linguistic term set; Consistency; Consensus; Hesitant fuzzy linguistic preference relation
Funding
- National Natural Science Foundation of China [71301110]
- Humanities and Social Sciences Foundation of the Ministry of Education [3XJC630015]
- Research Fund for the Doctoral Program of Higher Education of China [20130181120059]
- Fundamental Research Funds for the Central Universities [skqy201525]
- National Natural Science Foundation of China [71301110]
- Humanities and Social Sciences Foundation of the Ministry of Education [3XJC630015]
- Research Fund for the Doctoral Program of Higher Education of China [20130181120059]
- Fundamental Research Funds for the Central Universities [skqy201525]
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The use of hesitant information in pairwise comparisons enriches the flexibility of qualitative decision making and allows for hesitant fuzzy linguistic preference relation (HFLPR). This paper develops separate consistency and consensus processes to deal with HFLPR individual rationality and group rationality. First, a possibility distribution approach and a 2-tuple linguistic model are introduced as support tools. Then, a new consistency measure is defined and a convergent algorithm described to aid the consistency improvement process in a given HFLPR. The algorithm adopts a local revision strategy and can be easily interpreted. Further, a direct consensus reaching process is presented to solve the HFLPR consensus problems. A prominent characteristic of this consensus reaching process is that the feedback system is based directly on the consensus degrees, thereby reducing the proximity measure calculations. Finally, the proposed consistency and consensus processes are applied to an investment project selection problem. The results and an in-depth comparative analysis verify the potential use and effectiveness of the proposed methods. (C) 2015 Elsevier Ltd. All rights reserved.
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