An approach towards decision making and shortest path problems using the concepts of interval‐valued Pythagorean fuzzy information

Jan, Naeem; Aslam, Muhammad; Ullah, Kifayat; Mahmood, Tahir; Wang, Jun

doi:10.1002/int.22154

Cited by 18 publications

(5 citation statements)

References 43 publications

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“…In the future, we will extend the proposed approach to deal effectively with the MCDM problem involving Pythagorean fuzzy soft graphs, 63 interval‐valued PFGs, 64 simplified interval‐valued PFGs, 65 and other generalizations of PFGs. Furthermore, we will expand our approach to other fields such as pattern recognition, supply chain management, and so forth.…”

Section: Discussionmentioning

confidence: 99%

A novel multicriteria decision‐making approach based on Pythagorean fuzzy sets and graph theory

Meng

Lin

2022

Int J of Intelligent Sys

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Given the problem that the relations among alternatives or criteria cannot be handled well in multicriteria decision making, this paper applies the concept of Pythagorean fuzzy sets to the graph and develops a decision‐making approach based on Pythagorean fuzzy graphs (PFGs). First, the weights obtained from the Laplacian energy of PFGs are taken as the subjective weights of criteria. Then, a new Pythagorean fuzzy entropy measure is defined to compute the objective weights of criteria. Meanwhile, a combined weighting method is presented, which makes the criteria weights consist of subjective weights and objective weights. Furthermore, combined weights are applied to the decision‐making process and a graph‐based Pythagorean fuzzy decision‐making method is proposed. Compared with other existing techniques, the proposed approach considers the relations between alternatives and the relations between criteria simultaneously. Finally, an illustrative example is used to verify the approach and demonstrate its effectiveness. The results show that the alternative ranking obtained by the proposed approach is reliable and credible.

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Section: Discussionmentioning

confidence: 99%

A novel multicriteria decision‐making approach based on Pythagorean fuzzy sets and graph theory

Meng

Lin

2022

Int J of Intelligent Sys

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“…For the AHM operator, its aggregated values are greatly influenced by extreme values [50]. e GHM operator is capable of balancing the big differences among input values [51]. erefore, the GHM operator performs better than the AHM operator in some cases.…”

Section: Heronian Mean and Geometric Heronian Meanmentioning

confidence: 99%

MULTIMOORA Method for Addressing Security Algorithms Evaluation Problem under q-Rung Orthopair Fuzzy Environment

Wang

Lin

et al. 2022

Mathematical Problems in Engineering

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How to determine a suitable security algorithm for a special application scenario is a complex problem. In this paper, this complex problem is formulated as a multicriteria decision-making (MCDM) problem, and we propose a novel MULTIMOORA (multiobjective optimization on the basis of a ratio analysis plus the full MULTIpevaluation information in the security algorithms evaluation problem. The MULTIMOORA method is an excellent decision method, which owns strong robustness. However, it has not been used to process the complex information structure of q-rung orthopair fuzzy sets. Moreover, it cannot solve the problem that the extreme values negatively influence the ranking results, and it also cannot capture the interrelationship hiding behind the criteria. To overcome the above challenges, we propose novel q-rung orthopair fuzzy Dombi power Heronian mean (DPHM) operator and q-rung orthopair fuzzy Dombi power geometric Heronian mean (DPGHM) operator. Based on these two operators, the MULTIMOORA method is improved for solving the security algorithms’ evaluation problem. Finally, a practical example for evaluating five security algorithms is used to illustrate the decision process of the proposed q-rung orthopair fuzzy MULTIMOORA method.

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“…Shubatah [24] explored the notions of dominance and total domination in FGs. Jan et al [25] investigated interval-valued PFGs decision-making and shortest path issues. Pachamuthu and Praveenkumar [26] introduced the idea of dominance in IFGs of second type.…”

Section: Introductionmentioning

confidence: 99%

Graphical Analysis of q-Rung Orthopair Fuzzy Information with Application

AlSalman

Alkhamees

2022

Mathematical Problems in Engineering

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The q-rung orthopair fuzzy graph (q-ROFG) is an expansion of the intuitionistic fuzzy graph (IFG) and Pythagorean fuzzy graph (PFG); q-rung orthopair fuzzy model is an influential model for describing vagueness and uncertainty as a comparison to an intuitionistic fuzzy model and Pythagorean fuzzy model. The research aims to illustrate the notion of the graph of q-rung orthopair fuzzy sets (q-ROFSs). Furthermore, in this article, we examine the ideas of domination theory (DT) and double domination theory (DDT) in q-ROFGs. Additionally, the structure of q-ROFG is developed and its associated concept is presented through the assistance of instructive instances. Furthermore, the DT of q-ROFGs is established, as are cardinality, power, and completeness on dominance in a q-ROFG and bipartite q-ROFG, and double domination set (DDS), as well as some results, is investigated in the concept of q-ROFGs. A political campaign is simulated using the proposed structure as an application, and the impact of double dominance (DD) on political campaigns is investigated. Finally, a comparison is given between the proposed study and actual studies, as well as the advantages of working in the q-ROFG scenario.

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An approach towards decision making and shortest path problems using the concepts of interval‐valued Pythagorean fuzzy information

Cited by 18 publications

References 43 publications

A novel multicriteria decision‐making approach based on Pythagorean fuzzy sets and graph theory

A novel multicriteria decision‐making approach based on Pythagorean fuzzy sets and graph theory

MULTIMOORA Method for Addressing Security Algorithms Evaluation Problem under q-Rung Orthopair Fuzzy Environment

Graphical Analysis of q-Rung Orthopair Fuzzy Information with Application

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