Decision-Making Approach Based on Neutrosophic Rough Information

Akram, Muhammad; Ishfaq, Nabeela; Sayed, Sidra; Smarandache, Florentín

doi:10.3390/a11050059

Cited by 13 publications

(8 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…, and the same can be applied to the rest of Expression (21). Therefore, RNSCE A, A , B, B = RNSCE B, B , A, A , and the proof is completed.…”

Section: Rough Neutrosophic Symmetric Cross Entropy Measurementioning

confidence: 77%

“…Mohana and Mohanasundari [19] studied the properties and degree of similarity between two single-valued rough neutrosophic sets. Malik, Akram and Smarandache [20] developed soft, rough neutrosophic graphs and influence cycles and trees, using them in the decision-making process, while Akram et al [21] proposed digraphs based on the neutrosophic rough hybrid model. The concept of fuzzy equivalence on standard neutrosophic sets and rough standard neutrosophic sets was developed by Thao et al [22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hybrid MCDM Based on VIKOR and Cross Entropy under Rough Neutrosophic Set Theory

2021

View full text Add to dashboard Cite

Problems in real life usually involve uncertain, inconsistent and incomplete information. An example of such problems is strategic decision making with respect to remediation planning of historic pedestrian bridges. The multiple decision makers and experts, as well as the various mutually conflicting criteria, unknown criteria weights, and vagueness and duality in final decisions, provide motivation to develop a methodology that is able to resist the challenges implicit in this problem. Therefore, the aim of this research was to propose an algorithm based on the theory of rough neutrosophic sets in order to solve the problem of strategic planning with respect to the remediation of historic pedestrian bridges. A new multicriteria decision-making model is developed that is a fusion of rough set and neutrosophic set theory. A new cross entropy is proposed under a rough neutrosophic environment that does not possess the shortcomings of asymmetrical character and unknown occurrences. Additionally, a weighted rough neutrosophic symmetric cross entropy is proposed. Furthermore, a rough neutrosophic VIKOR method is introduced, with which the values of the utility measure, regret measure and VIKOR index are obtained. These values, as well as the weighted rough neutrosophic symmetric cross entropy measure, are used to provide a ranking of historic pedestrian bridges favorable to remediation. Finally, an illustrative example of the strategic planning of remediation for historic pedestrian bridges is solved and compared to other research, demonstrating the robustness, feasibility and efficacy of the model when dealing with complex multicriteria decision-making processes.

show abstract

“…, and the same can be applied to the rest of Expression (21). Therefore, RNSCE A, A , B, B = RNSCE B, B , A, A , and the proof is completed.…”

Section: Rough Neutrosophic Symmetric Cross Entropy Measurementioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Hybrid MCDM Based on VIKOR and Cross Entropy under Rough Neutrosophic Set Theory

2021

View full text Add to dashboard Cite

show abstract

“…Finally, a numerical example for the safety assessment of construction projects was proposed to illustrate the new method and some comparisons were also conducted to further illustrate the advantages of the new method. In the future, the application of the proposed models and methods of 2TLNNs can be investigated in MAGDM problems [42][43][44][45][46][47][48][49][50][51][52][53], risk analysis and many other uncertain and fuzzy environments [54][55][56][57][58][59][60][61][62][63][64][65].…”

Section: Discussionmentioning

confidence: 99%

TODIM Method for Multiple Attribute Group Decision Making under 2-Tuple Linguistic Neutrosophic Environment

2018

View full text Add to dashboard Cite

In this article, we extend the original TODIM (Portuguese acronym for Interactive Multi-Criteria Decision Making) method to the 2-tuple linguistic neutrosophic fuzzy environment to propose the 2TLNNs TODIM method. In the extended method, we use 2-tuple linguistic neutrosophic numbers (2TLNNs) to present the criteria values in multiple attribute group decision making (MAGDM) problems. Firstly, we briefly introduce the definition, operational laws, some aggregation operators and the distance calculating method of 2TLNNs. Then, the calculation steps of the original TODIM model are presented in simplified form. Thereafter, we extend the original TODIM model to the 2TLNNs environment to build the 2TLNNs TODIM model, our proposed method, which is more reasonable and scientific in considering the subjectivity of DM’s behaviors and the dominance of each alternative over others. Finally, a numerical example for the safety assessment of a construction project is proposed to illustrate the new method, and some comparisons are also conducted to further illustrate the advantages of the new method.

show abstract

“…They pointed out that the simplest constraint is that the sum of the three degrees must not exceed 1. This constraint allows PFSs to have a different structure than neutrosophic sets (see: Akram et al 2018;Kamacı 2020;Riaz and Hashmi 2020;Smarandache 1998;Tehrim and Riaz 2019 for neutrosophic sets). In addition, many researchers derived various aggregation operators to aggregate the picture fuzzy aggregation information, e.g., the picture fuzzy aggregation operators and picture fuzzy Hamacher aggregation operators (Wei 2017(Wei , 2018, the picture fuzzy aggregation operators based on Einstein operations (Khan et al 2019b), and the picture fuzzy hybrid averaging operator (Garg 2017).…”

Section: Introductionmentioning

confidence: 99%

Dynamic aggregation operators and Einstein operations based on interval-valued picture hesitant fuzzy information and their applications in multi-period decision making

2021

View full text Add to dashboard Cite

The traditional picture hesitant fuzzy aggregation operators are generally suitable for aggregating information acquired in the form of picture hesitant fuzzy numbers, but they will fail in dealing with interval-valued picture hesitant fuzzy information. In this paper, we describe the notion of interval-valued picture hesitant fuzzy set and the operational laws of interval-valued picture hesitant fuzzy variables. Moreover, we derive some dynamic interval-valued picture hesitant fuzzy aggregation operators (based on Einstein operators) to aggregate the interval-valued picture hesitant fuzzy information collected at different periods. Some desirable properties of these aggregation operators are discussed in detail. In addition, we develop the approaches to tackle the multi-period decision-making problems, where all decision information takes the form of interval-valued picture hesitant fuzzy information collected at different periods. In an attempt to illustrate the applications of the proposed approaches, two numerical examples are given to measure the impact of Coronavirus Disease 2019 (COVID-19) in daily life and to identify the optimal investment opportunity. Finally, a comparative analysis of the proposed and existing studies are conducted to demonstrate the effectiveness of the proposed approaches. The presented interval-valued picture hesitant fuzzy operations, aggregation operators, and decision-making approaches can widely apply to dynamic decision analysis and multi-stage decision analysis in real life.

show abstract

Decision-Making Approach Based on Neutrosophic Rough Information

Cited by 13 publications

References 27 publications

Hybrid MCDM Based on VIKOR and Cross Entropy under Rough Neutrosophic Set Theory

Hybrid MCDM Based on VIKOR and Cross Entropy under Rough Neutrosophic Set Theory

TODIM Method for Multiple Attribute Group Decision Making under 2-Tuple Linguistic Neutrosophic Environment

Dynamic aggregation operators and Einstein operations based on interval-valued picture hesitant fuzzy information and their applications in multi-period decision making

Contact Info

Product

Resources

About