Selection of Suitable Automatic CPR Device Chassis Material Using Intuitionistic Fuzzy TOPSIS, VIKOR, and CODAS Methods

Kağızman, Ahmet; Deveci, Kaan; Sezer, Volkan

doi:10.2139/ssrn.4200130

SSRN Journal

2022

DOI: 10.2139/ssrn.4200130

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Selection of Suitable Automatic CPR Device Chassis Material Using Intuitionistic Fuzzy TOPSIS, VIKOR, and CODAS Methods

Ahmet Kağızman

Kaan Deveci

Volkan Sezer

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2024

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Solution strategy for sustainable additive manufacturing design problem using Pythagorean fuzzy MCGDM methodology

Momena

2024

Complex Intell. Syst.

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To solve difficulties involving various groups’ decision-making problems, this work has been proposed to develop a logical aggregation approach to aggregate decision-makers’ crisp data into Pythagorean fuzzy numbers. By combining the established strategy with the Pythagorean fuzzy TOPSIS method, a hybrid Pythagorean fuzzy multiple criteria group decision-making methodology is presented. Based on fuzzy rules inference and the Takagi–Sugeno technique, a novel function is created to represent the degrees of uncertainty in decision-makers’ data. As an example, the material selection process in practical additive manufacturing designs is provided to show how the proposed methodology may be applied to actual applications. Sensitivity analysis is used to evaluate the effectiveness of the suggested methodology. The outcomes demonstrate that the plan was successful in producing a PFN that accurately reflects the decision-maker’s knowledge.

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Solution strategy for sustainable additive manufacturing design problem using Pythagorean fuzzy MCGDM methodology

Momena

2024

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

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Selection of Suitable Automatic CPR Device Chassis Material Using Intuitionistic Fuzzy TOPSIS, VIKOR, and CODAS Methods

Cited by 1 publication

References 40 publications

Solution strategy for sustainable additive manufacturing design problem using Pythagorean fuzzy MCGDM methodology

Solution strategy for sustainable additive manufacturing design problem using Pythagorean fuzzy MCGDM methodology

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