Abstract
Many models handle uncertainty problems. Fuzzy set (FS) is one of them. The next one is intuitionistic fuzzy set (IFS). Further generalization is interval-valued fuzzy set (IVFS). But all those models had some difficulty due to lack of parameterization tool, which motivated mathematician Molodtsov to introduce soft set model in 1999. Hybrid models of these models are more efficient. Interval-valued intuitionistic fuzzy soft set (IVIFSS) introduced by Jiyang. Following their characteristic function approach Tripathy et al. introduced fuzzy soft set as a hybrid model in 2015. Here, we continue this further to define IVI fuzzy soft sets (IVIFSS). Many related concepts like complement, null, and absolute IVIFSS are introduced and operations like intersection and union of IVIFSSs are also redefined. Recently, soft set is applied in various forms to derive decision-making (DM) by Tripathy et al. We extend it further by proposing an algorithm which uses IVIFSS in order to achieve DM. These algorithms are much improved and applicable than that of Jiyang. Also, it generalizes all the previous algorithms in this direction.
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Mohanty, R.K., Sooraj, T.R., Tripathy, B.K. (2017). IVIFS and Decision-Making. In: Satapathy, S., Bhateja, V., Joshi, A. (eds) Proceedings of the International Conference on Data Engineering and Communication Technology. Advances in Intelligent Systems and Computing, vol 468. Springer, Singapore. https://doi.org/10.1007/978-981-10-1675-2_33
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DOI: https://doi.org/10.1007/978-981-10-1675-2_33
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