Choquet integrals of weighted generalized and group generalized intuitionistic fuzzy soft sets
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For many real multi-criteria decision-making (MCDM) problems under intuitionistic fuzzy environment, most criteria have interactive characteristics so that it is not suitable for us to aggregate them by traditional aggregation operators based on additive measures. To approximate the human subjective decision-making process, this paper puts forward the new aggregation operators of generalized intuitionistic fuzzy soft set (GIFSS) and group generalized intuitionistic fuzzy soft sets (G-GIFSS) through the Chqouet integral. These new operators not only demonstrate the interaction phenomena among elements, experts (or moderators) or the ordered positions of them, but also consider their importance or the order positions of them. Furthermore, the new operators are not necessary to assume additivity and independence among decision-making criteria. It should be noted that the existing aggregation operators of GIFSS and G-GIFSS are special cases of the new Choquet integral operators. Two Choquet integral operator-based approaches are developed to solve the MCDM under the intuitionistic fuzzy soft set environment. Finally, a practical example of MCDM is given to validate the effectiveness of the proposal.
KeywordsChoquet integral GIFSS G-GIFSS Aggregation operators Correlations
This study was funded by National Natural Science Foundation of China (Grant No. 61490702).
Compliance with ethical standards
Conflict of interest
Sheng Li declares that he has no conflict of interest. Xiao-qi Peng declares that she has no conflict of interest. Yu-xiao Li declares that she has no conflict of interest.
This article does not contain any studies with human participants performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
- Agarwal M, Hanmandlu M, Biswas KK (2011) Generalized intuitionistic fuzzy soft set and its application in practical medical diagnosis problem. In: 2011 IEEE international conference on fuzzy systems (FUZZ). IEEE, pp 2972–2978Google Scholar
- Babitha KV, Sunil JJ (2011) Generalized intuitionistic fuzzy soft sets and its applications. Gen Math Notes 7:1–14Google Scholar
- Dinda B, Bera T, Samanta TK (2010) Generalised intuitionistic fuzzy soft sets and its application in decision making. arXiv preprint arXiv:1010.2468
- Geng S, Li Y, Feng F et al (2011) Generalized intuitionistic fuzzy soft sets and multiattribute decision making. In: 2011 4th international conference on biomedical engineering and informatics (BMEI), vol 4. IEEE, pp 2206–2211Google Scholar
- Wu H, Su X (2015) Threat assessment of aerial targets based on group generalized intuitionistic fuzzy soft sets. Control Decis 30(8):1462–1468Google Scholar
- Zadeh LA (1996) Fuzzy sets. In: Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A Zadeh, pp 394–432Google Scholar