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Book ChapterDOI

IVIFS and Decision-Making

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TLDR
This work defines IVI fuzzy soft sets (IVIFSS) and proposes an algorithm which uses IVIFSS in order to achieve decision-making (DM) and generalizes all the previous algorithms in this direction.
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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Citations
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Journal ArticleDOI

A novel VIKOR method with an application to multiple criteria decision analysis for hospital-based post-acute care within a highly complex uncertain environment

TL;DR: The present study provides several significant contributions, such as structuring the selection problem for hospital-based PAC, extending the IVPF theory and VIKOR to the medical and healthcare fields, simplifying the manipulation procedure in handling IVPF information, constructing valuable concepts of remoteness-based indices, and developing an effective IVPFVIKOR ranking procedure.
Book ChapterDOI

Hesitant Fuzzy Soft Set Theory and Its Application in Decision Making

TL;DR: This paper redefined the hesitant fuzzy soft sets (HFSS) with the help of membership function and provides a decision making algorithm.
Book ChapterDOI

Interval Valued Hesitant Fuzzy Soft Sets and Its Application in Stock Market Analysis

TL;DR: This paper extends the concept of interval valued fuzzy soft set by introducing interval valued hesitant fuzzy soft sets (IVHFSS) through the membership function approach introduced by Tripathy et al. in 2015.
Journal ArticleDOI

An Interval Valued Fuzzy Soft Set Based Optimization Algorithm for High Yielding Seed Selection

TL;DR: As seed selectionﻵ�is-is theﻴ�firstﻰ�attempt﻽� forソsuchﻷ such-and-a-half-year-old-girls-of-elderly-age-in-need-to-be-saved-by-the-seeds, £10,000-£15,000 is invested in this study.
Journal ArticleDOI

Group Decision Making Through Interval Valued Intuitionistic Fuzzy Soft Sets

TL;DR: The authors propose a group decision making algorithm using IVIFSS, which generalises many of the earlier algorithms and compute its complexity and establish the computation experimentally with graphical illustrations.
References
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Book

Fuzzy sets

TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Journal ArticleDOI

Intuitionistic fuzzy sets

TL;DR: Various properties are proved, which are connected to the operations and relations over sets, and with modal and topological operators, defined over the set of IFS's.
Journal ArticleDOI

Soft set theory—First results

TL;DR: The main purpose of this paper is to introduce the basic notions of the theory of soft sets, to present the first results of the the theory, and to discuss some problems of the future.
Journal ArticleDOI

Soft set theory

TL;DR: The authors define equality of two soft sets, subset and super set of a soft set, complement of asoft set, null soft set and absolute soft set with examples and De Morgan's laws and a number of results are verified in soft set theory.
Journal ArticleDOI

An application of soft sets in a decision making problem

TL;DR: In this article, the theory of soft sets was applied to solve a decision-making problem using rough mathematics, and the results showed that soft sets can be used to solve decision making problems.
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