Decision making has become a common feature in day-to-day activities. Uncertainty-based models are more efficient in handling such problems. In this chapter, we propose an algorithm in this direction by using a hybrid model formed by combining the two models of soft set (SS) and the intuitionistic fuzzy set (IFS). We follow the characteristic function approach used by Tripathy et al. for the purpose. The illustrative real-life example shows the efficiency of our algorithm over other such models. © Springer Nature Singapore Pte Ltd. 2018.

Balakrushna Tripathy

Department of Analytics

School of Computer Science and Engineering

Vellore Campus

Sooraj T.R

Mohanty R.K

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Improved Decision Making Through IFSS

Smart Computing and Informatics Smart Innovation, Systems and Technologies

There are several models of uncertainty found in the literature like fuzzy set, rough set, soft set and hesitant fuzzy set. Also, several hybrid models have come up as a combination of these models and have been found to be more useful than the individual models. In everyday life we make many decisions. Making efficient decisions under uncertainty needs better techniques. Many such techniques have been developed in the recent past. These techniques involve soft sets and fuzzy sets. In this paper we redefined the hesitant fuzzy soft sets (HFSS) with the help of membership function. We also provide a decision making algorithm. © Springer Nature Singapore Pte Ltd. 2017.

Advances in Intelligent Systems and Computing Artificial Intelligence and Evolutionary Computations in Engineering Systems

Hesitant Fuzzy Soft Set Theory and Its Application in Decision Making

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. © Springer Science+Business Media Singapore 2017.

Proceedings of the International Conference on Data Engineering and Communication Technology Advances in Intelligent Systems and Computing

IVIFS and Decision-Making

Molodtsov introduced soft set theory in 1999 to handle uncertainty. It has been found that hybrid models are more useful than that of individual components. Yang et al. introduced the concept of interval valued fuzzy soft set (IVFSS) by combining the interval valued fuzzy sets (IVFS) and soft set model. In this paper we extend it by introducing interval valued hesitant fuzzy soft sets (IVHFSS) through the membership function approach introduced by Tripathy et al. in 2015. To illustrate the application of the new model, we provide a decision making algorithm and use it in stock market analysis. © Springer Nature Singapore Pte Ltd. 2017.

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

Soft computing techniques are innovative tools that use nature-inspired algorithms to run predictive analysis of industries from business to software measurement. These tools have gained momentum in recent years for their practicality and flexibility. The Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making collects both empirical and applied research in the field of fuzzy set theory, and bridges the gap between the application of soft computational approaches and the organizational decision making process. This publication is a pivotal reference for business professionals, IT specialists, software engineers, and advanced students of business and information technology. © 2017 by IGI Global. All rights reserved.

Advances in Business Strategy and Competitive Advantage

Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making

Soft set (SS) 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 interval-valued fuzzy set (IVFS) was introduced as an extension of fuzzy set (FS) by Zadeh. Yang introduced the concept of IVFSS by combining and soft set models. Here, we define IVFSS through the membership function approach to define soft set by Tripathy et al. very recently. Several concepts, such as complement of an IVFSS, null IVFSS, absolute IVFSS, intersection, and union of two IVFSSs, are redefined. To illustrate the application of IVFSSs, a decision-making (DM) algorithm using this notion is proposed and illustrated through an example. © Springer Science+Business Media Singapore 2017.

Journal	Data powered by TypesetSmart Computing and Informatics Smart Innovation, Systems and Technologies
Publisher	Data powered by TypesetSpringer Singapore
ISSN	2190-3018
Open Access	0