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A random intuitionistic fuzzy factor analysis model for complex multi-attribute large group decision-making in dynamic environments
journal contribution
posted on 2021-03-30, 14:22 authored by Xiaohong Chen, Mengjing Wu, Chunqiao Tan, Tao ZhangTao ZhangThe challenge of complex multi-attribute large group decision-making (CMALGDM) is reflected from three perspectives: interrelated attributes, large group decision makers (DMs) and dynamic decision environments. However, there are few decision techniques that can address the three perspectives simultaneously. This paper proposes a random intuitionistic fuzzy factor analysis model, aiming to address the challenge of CMALGDM from the three perspectives. The proposed method effectively reduces the dimensionality of the original data and takes into account the underlying random environmental factors which may affect the performances of alternatives. The development of this method follows three steps. First, the random intuitionistic fuzzy variables are developed to deal with a hybrid uncertain situation where fuzziness and randomness co-exist. Second, a novel factor analysis model for random intuitionistic fuzzy variables is proposed. This model uses specific mappings or functions to define the way in which evaluations are affected by the dynamic environment vector through data learning or prior distributions. Third, multiple correlated attribute variables and DM variables are transformed into fewer independent factors by a two-step procedure using the proposed model. In addition, the objective classifications and weights for attributes and DMs are obtained from the results of orthogonal rotated factor loading. An illustrative case and detailed comparisons of decision results in different environmental conditions are demonstrated to test the feasibility and validity of the proposed method.
Funding
Major Project of National Nature Science Foundation of China (71790615)
National Nature Science Foundation of China (71671188, 71971218)
Key Project of National Nature Science Foundation of China (91846301)
Key Laboratory of Hunan Province for New Retail Virtual Reality Technology, Hunan University of Technology and Business (2017TP1026)
History
School
- Loughborough University London
Published in
Fuzzy Optimization and Decision MakingVolume
20Issue
1Pages
101 - 127Publisher
SpringerVersion
- VoR (Version of Record)
Rights holder
© SpringerPublisher statement
This is a post-peer-review, pre-copyedit version of an article published in Fuzzy Optimization and Decision Making. The final authenticated version is available online at: https://doi.org/10.1007/s10700-020-09334-9.Acceptance date
2020-05-19Publication date
2020-07-17Copyright date
2020ISSN
1568-4539eISSN
1573-2908Publisher version
Language
- en