A consensus model based on rough bipolar fuzzy approximations

Malik, Nosheen; Shabir, Muhammad

doi:10.3233/jifs-181223

Cited by 14 publications

(10 citation statements)

References 27 publications

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“…Malik and Shabir [44] initiated the idea of rough fuzzy BSSs and applied this idea to solve DM problems. Also, Malik and Shabir [45] developed a consensus model based on rough bipolar fuzzy approximations. Mahmood [39] redefined a version of BSSs which is called T-bipolar soft sets and applied this idea in DM problems.…”

Section: A Literature Reviewmentioning

confidence: 99%

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A Novel Approach Toward Roughness of Bipolar Soft Sets and Their Applications in MCGDM

et al. 2021

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The uncertainty in the data is an obstacle in decision-making (DM) problems. In order to solve problems with a variety of uncertainties a number of useful mathematical approaches together with fuzzy sets, rough sets, soft sets, bipolar soft sets have been developed. The rough set theory is an effective technique to study the uncertainty in data, while bipolar soft sets have the ability to handle the vagueness, as well as bipolarity of the data in a variety of situations. This study develops a new methodology, which we call the theory of dominance-based bipolar soft rough sets (DB-BSRSs), which will be used to propose a new technique to solve decision-making problems. The idea introduced in this study has never been discussed earlier. Furthermore, this concept has been explored by means of a detailed study of the structural properties. Moreover, some important measures like the accuracy measure, the measure of precision, and the measure of quality for DB-BSRSs are also provided. Finally, an application of the DB-BSRSs in multicriteria group decision-making (MCGDM) problem is presented and an algorithm for this application is proposed, supported by an example, which yields the best decision, as well as, the worst decision between some objects. In comparison with some existing results, we also present some advantages of our proposed method.

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Section: A Literature Reviewmentioning

confidence: 99%

“…Shabir et al [56] reclassified a model of a soft rough set known as a modified soft rough set (MRSset). Majumdar and Samanta [45] introduced the idea of soft mapping and studied some of its properties. They applied soft mapping in medical diagnosis.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach Toward Roughness of Bipolar Soft Sets and Their Applications in MCGDM

et al. 2021

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“…Two approximation sets partition the universal set into three portions: the positive portion, negative portion, and boundary portion. Numerous significant extensions, including rough set models based on tolerance relation, soft binary relation, reflexive relation, the soft rough set model, bipolar soft rough set model, fuzzy rough set model, bipolar fuzzy rough set model, rough fuzzy soft set model, rough bipolar fuzzy soft set model, [11][12][13] have been proposed in the past 20 years to enlarge the application spectrum of Pawlak's rough set concept.…”

Section: Introductionmentioning

confidence: 99%

“…There is a mapping for measuring positive information, and a mapping for measuring negative information. In order to understand the roughness of BFSs, one attempt has been made by Malik and Shabir [12]. They used only one equivalence relation and one universe to solve decision making problems.…”

Section: Introductionmentioning

confidence: 99%

A novel multigranulation roughness of bipolar fuzzy set over dual universes and its applications

2023

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In the world, multigranulation rough sets and bipolar fuzzy sets are the practical tools for dealing with the uncertainty, vagueness, and imperfection that frequently arise in decision mak- ing problems. The goal of multigranulation rough sets is to characterize uncertain situations in var- ious granularity spaces, whereas bipolar fuzzy sets (BFSs) have the capacity to handle uncertainty as well as informational bipolarity in a variety of contexts. This article examines the optimistic multigranulation rough approximation of a BFS in the light of multi-soft binary relations across two different universes. We investigate some algebraic properties of our newly constructed optimistic multigranulation rough set scheme. Measures of accuracy and roughness are also covered in this paper. Finally, two decision algorithms are designed with respect to aftersets and foresets that are applied to a decision making problem in disease diagnoses, and the applicability of the method is illustrated by a numerical example.

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“…In [33], Malik and Shabir pioneered the concept of rough fuzzy BSS and used them to rectify DM problems. Malik and Shabir [34] created a consensus model using rough bipolar fuzzy approximations. Al-Shami [35] conceived the idea of belonging and non-belonging relations between a BSS and an ordinary point.…”

Section: Introductionmentioning

confidence: 99%

Novel Bipolar Soft Rough-Set Approximations and Their Application in Solving Decision-Making Problems

Gul

Shabir

Mashwani

et al. 2022

IJFIS

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The rough set (RS) theory is a successful approach for studying the uncertainty in data. In contrast, the bipolar soft sets (BSS) can deal with the uncertainty, as well as bipolarity of the data in many situations. In 2018, Karaaslan and C ¸agman proposed bipolar soft rough sets (BSRSs), a hybridization of RS and BSS. However, certain shortcomings with BSRS violate Pawlak's RS theory. To overcome these shortcomings, the concept of the modified bipolar soft rough set (MBSRS) has been proposed in this study. Moreover, this idea has been investigated through illustrative examples, where the important properties are inspected deeply. Furthermore, certain significant measures associated with MBSRS are also provided. Finally, an application of the MBSRS to multi-attribute group decision-making (MAGDM) problems is proposed. In addition, among various alternatives, an algorithm for decisionmaking accompanied by a practical example is presented as the optimal alternative . A brief comparative analysis of the proposed approach with some existing techniques is also provided to indicate the validity, flexibility, and superiority of the suggested MAGDM model.

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A consensus model based on rough bipolar fuzzy approximations

Cited by 14 publications

References 27 publications

A Novel Approach Toward Roughness of Bipolar Soft Sets and Their Applications in MCGDM

A Novel Approach Toward Roughness of Bipolar Soft Sets and Their Applications in MCGDM

A novel multigranulation roughness of bipolar fuzzy set over dual universes and its applications

Novel Bipolar Soft Rough-Set Approximations and Their Application in Solving Decision-Making Problems

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