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Fuzzy Soft Set Theory and Its Application in Group Decision Making
Sooraj T.R, Mohanty R.K,
Published in Springer Singapore
Volume: 452
Pages: 171 - 178
Soft set theory was introduced by Molodtsov to handle uncertainty. It uses a family of subsets associated with each parameter. Hybrid models have been found to be more useful than the individual components. Earlier fuzzy set and soft set were combined to form fuzzy soft sets (FSS). Soft sets were defined from a different point of view in Tripathy et al. (Int J Reasoning-Based Intell Syst 7(3/4), 224–253, 2015) where they used the notion of characteristic functions. Hence, many related concepts were also redefined. In Tripathy et al. (Proceedings of ICCIDM-2015, 2015) membership function for FSSs was defined. We propose a new algorithm by following this approach which provides an application of FSSs in group decision making. The performance of this algorithm is substantially improved than that of the earlier algorithm. © Springer Science+Business Media Singapore 2016.
About the journal
JournalData powered by TypesetAdvanced Computing and Communication Technologies Advances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Singapore
Open Access0