A Novel Decision-Making Method Based on Rough Fuzzy Information

Zafar, Fariha; Akram, Muhammad

doi:10.1007/s40815-017-0368-0

Cited by 78 publications

(33 citation statements)

References 28 publications

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“…Naz et al [19,20] discussed some basic notions of single valued neutrosophic graphs along with its application in multi criteria decision-making. More recently, Akram et al introduced many new concepts related to m-polar fuzzy graph, fuzzy soft graph, rough fuzzy graph, neutrosophic graph and their extensions [21][22][23][24][25]. This paper proposes a new graph, called Pythagorean fuzzy graph (PFG).…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach to Decision-Making with Pythagorean Fuzzy Information

2018

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A Pythagorean fuzzy set (PFS) is a powerful tool for depicting fuzziness and uncertainty. This model is more flexible and practical as compared to an intuitionistic fuzzy model. This paper proposes a new graph, called Pythagorean fuzzy graph (PFG). We investigate some properties of our proposed graphs. We determine the degree and total degree of a vertex of PFGs. Furthermore, we present the concept of Pythagorean fuzzy preference relations (PFPRs). In particular, we solve decision-making problems, including evaluation of hospitals, partner selection in supply chain management, and electronic learning main factors evaluation by using PFGs.

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Section: Introductionmentioning

confidence: 99%

A Novel Approach to Decision-Making with Pythagorean Fuzzy Information

2018

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“…Akram and Shahzadi [25] have introduced neutrosophic soft graphs. Zafar and Akram [26] introduced a rough fuzzy digraph and several basic notions concerning rough fuzzy digraphs. In this research paper, a neutrosophic soft rough set is a generalization of a neutrosophic rough set, and we introduce the idea of neutrosophic soft rough graphs (NSRGs) that are made by combining NSRSs with graphs and describe different methods of their construction.…”

Section: Introductionmentioning

confidence: 99%

Neutrosophic Soft Rough Graphs with Application

Akram

Malik

Shahzadi

et al. 2018

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Neutrosophic sets (NSs) handle uncertain information while fuzzy sets (FSs) and intuitionistic fuzzy sets (IFs) fail to handle indeterminate information. Soft set theory, neutrosophic set theory, and rough set theory are different mathematical models for handling uncertainties and they are mutually related. The neutrosophic soft rough set (NSRS) model is a hybrid model by combining neutrosophic soft sets with rough sets. We apply neutrosophic soft rough sets to graphs. In this research paper, we introduce the idea of neutrosophic soft rough graphs (NSRGs) and describe different methods of their construction. We consider the application of NSRG in decision-making problems. In particular, we develop efficient algorithms to solve decision-making problems.

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“…Akram et al [13][14][15][16] considered several new concepts of neutrosophic graphs with applications. Zafer and Akram [17] introduced a novel decision-making method based on rough fuzzy information. In this research study, we apply the concept of rough neutrosophic sets to graphs.…”

Section: Introductionmentioning

confidence: 99%

Rough Neutrosophic Digraphs with Application

Sayed

Ishfaq

Akram

et al. 2018

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Abstract:A rough neutrosophic set model is a hybrid model which deals with vagueness by using the lower and upper approximation spaces. In this research paper, we apply the concept of rough neutrosophic sets to graphs. We introduce rough neutrosophic digraphs and describe methods of their construction. Moreover, we present the concept of self complementary rough neutrosophic digraphs. Finally, we consider an application of rough neutrosophic digraphs in decision-making.

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A Novel Decision-Making Method Based on Rough Fuzzy Information

Cited by 78 publications

References 28 publications

A Novel Approach to Decision-Making with Pythagorean Fuzzy Information

A Novel Approach to Decision-Making with Pythagorean Fuzzy Information

Neutrosophic Soft Rough Graphs with Application

Rough Neutrosophic Digraphs with Application

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