Multi-criteria Group Decision-Making Based on Interval Neutrosophic Uncertain Linguistic Variables and Choquet Integral
The interval neutrosophic uncertain linguistic variables (INULVs) can be better at handling the uncertainty of the decision-makers’ cognition in multi-criteria group decision-making (MCGDM) problems. Most MCGDM methods with INULVs are based on the supposition that all criteria are independent; however, they may be correlative in real decisions. The Choquet integral can process MCGDM problems with correlated criteria, which fail to aggregate INULVs. So, it is necessary and meaningful to propose the MCGDM method with INULVs based on the Choquet integral by considering the correlations between the attributes.
By combining INULVs with the Choquet integral, we propose the interval neutrosophic uncertain linguistic Choquet averaging (INULCA) operator and the interval neutrosophic uncertain linguistic Choquet geometric (INULCG) operator. These two operators reflect the existing correlation between two adjacent coalitions. In order to globally consider the correlations between elements or their ordered positions, the generalized Shapley INULCA (GS-INULCA) operator and the generalized Shapley INULCG (GS-INULCG) operator are further proposed. Furthermore, some models based on the grey relational analysis (GRA) method for determining the optimal fuzzy measures on the expert set and the criteria set are respectively built.
Based on the proposed operators and built models, a method is developed to cope with the MCGDM problems with INULVs, and the validity and advantages of the proposed method are analyzed by comparison with some existing approaches.
The method proposed in this paper can effectively handle the MCGDM problems in which the attribute information is expressed by INULVs, the attributes’ and experts’ weights are partly known, and the experts and attributes are interactive.
KeywordsMultiple-criteria group decision-making (MCGDM) Interval neutrosophic uncertain linguistic set Grey relational analysis Choquet integral Generalized Shapley function Fuzzy measure
This paper is supported by the National Natural Science Foundation of China (Nos. 71471172 and 71271124), the Special Funds of Taishan Scholars Project of Shandong Province, National Soft Science Project of China (2014GXQ4D192), Shandong Provincial Social Science Planning Project (15BGLJ06), and the science and technology project of colleges and universities in Shandong Province (J13LN19 and J16LN25).
Compliance with Ethical Standards
Conflict of interest
Peide Liu and Guolin Tang declare that they have no conflict of interest.
Informed Consent was not required as no human or animals were involved.
Human and Animals Rights
This article does not contain any studies with human participants or animals performed by any of the authors.
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