An approach to multi-attribute decision-making based on intuitionistic fuzzy soft information and Aczel-Alsina operational laws

Ali, Amir S.; Ullah, Kifayat; Hussain, Amir

doi:10.31181/jdaic10006062023a

Cited by 49 publications

(8 citation statements)

References 38 publications

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“…To validate these results, a verification process will be applied, employing identical initial fuzzy decision matrix for alternatives and the identical criteria weights (Ali et al, 2023;Naseem et al, 2023;Więckowski et al, 2023). This approach aims to assess how specific steps in alternative methods impact the final ranking of tractors.…”

Section: Resultsmentioning

confidence: 99%

Application of Fuzzy-Rough Approach in Tractor Selection

Puška,

Štilić,

Nedeljković

et al. 2024

JCCE

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The process of selecting a tractor exemplifies decision-making in a multi-criteria context. With the integration of the fuzzy-rough concept, this article employs a hybrid multi-criteria decision-making methodology. The fuzzy-rough approach is employed to facilitate decision-making with imprecise information, incorporating uncertainty while mitigating the subjectivity inherent in expert judgments. The Logarithm Methodology of Additive Weights (LMAW) method is utilized to evaluate the importance of criteria influencing the evaluation of selected tractors. Subsequently, the Simple Additive Weighting (SAW) method is employed to identify the optimal tractor aligning with the specified criteria. Among the five observed tractors, the Solis S 26 exhibited the most favorable results. Sensitivity analysis and result validation support the validity of the results obtained. Result validation involves a comparison of fuzzy-rough SAW outcomes with alternative methods utilizing the fuzzy-rough approach, while the influence of criteria importance on the decision's final outcome was examined through sensitivity analysis. This paper contributes to comprehending the fuzzy-rough concept's applicability in multi-criteria decision-making. Demonstrated flexibility of the fuzzy-rough methodology suggests its potential for future research reliant on imprecise data, uncertainty incorporation, and subjectivity reduction in decision-making processes.

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Section: Resultsmentioning

confidence: 99%

Application of Fuzzy-Rough Approach in Tractor Selection

Puška,

Štilić,

Nedeljković

et al. 2024

JCCE

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“…Results of the fuzzy-rough MARCOS method. In order to confirm the quality of their models, more and more authors have included in their research a comparative analysis of their results with results obtained using other methods, such as in [53][54][55][56]. In order to test the results of this research, other MCDM methods in the fuzzy-rough form were applied, namely SAW (Simple Additive Weighting), ARAS (Additive Ratio Assessment), CRADIS, MABAC, and WPM (Weighted Product Method).…”

Section: Resultsmentioning

confidence: 99%

Multi-Criteria Selection of Electric Delivery Vehicles Using Fuzzy–Rough Methods

Wang,

Xu,

Puška

et al. 2023

Sustainability

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Urban logistics implementation causes environmental pollution; therefore, it is necessary to consider the impact on the environment when carrying out such logistics. Electric vehicles are alternative vehicles that reduce the impact on the environment. For this reason, this study investigated which electric vehicle has the best indicators for urban logistics. An innovative approach when selecting such vehicles is the application of a fuzzy–rough method based on expert decision making, whereby the decision-making process is adapted to the decision makers. In this case, two methods of multi-criteria decision making (MCDM) were used: SWARA (stepwise weight assessment ratio analysis) and MARCOS (measurement alternatives and ranking according to compromise solution). By applying the fuzzy–rough approach, uncertainty is included when making a decision, and it is possible to use linguistic values. The results obtained by the fuzzy–rough SWARA method showed that the range and price of electric vehicles have the greatest influence on the selection of an electric delivery vehicle. The results of applying the fuzzy–rough MARCOS method indicated that the Kangoo E-Tech Electric vehicle has the best characteristics according to experts’ estimates. These results were confirmed by validation and the application of sensitivity analysis. In urban logistics, the selection of an electric delivery vehicle helps to reduce the impact on the environment. By applying the fuzzy–rough approach, the decision-making problem is adjusted to the preferences of the decision makers who play a major role in purchasing a vehicle.

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“…Therefore, many real life problems are modelled and optimized in a fuzzy based uncertain environment. As the classical fuzzy sets and numbers may have some shortcomings and may not be able to reflect some high degrees of uncertainty, this theory has been developed and modified in the literature (Ali et al, 2023;Naseem et al, 2023;Mahmoodirad and Niroomand, 2023). For this aim, some newer types of fuzzy sets, such as type-2 fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets, etc., have been introduced in the literature (Wang et al, 2023;Mishra et al, 2023).…”

Section: Basic Conceptsmentioning

confidence: 99%

Interval-Valued Pythagorean Fuzzy Extension of DEMATEL for Prioritizing and Casualty Analysis of Environmental Criteria of Organizational Behaviour in Higher Education Sector

Torkzadeh,

Pamucar,

Niroomand

2023

Informatica

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In this study, effect of the environmental factors on the organizational behaviour in higher education sector is analysed and these factors are prioritized. For this aim, first, the environmental criteria affecting the organizational behaviour of higher education sector are selected from the literature. Then, as a solution methodology, (i) some experts are asked to determine pairwise comparison of the criteria, (ii) the linguistic terms are converted to interval-valued Pythagorean fuzzy values, and (iii) an interval-valued Pythagorean fuzzy DEMATEL approach is developed and applied. According to the results, most of the economic, political, and professional domain criteria are of the cause category.

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An approach to multi-attribute decision-making based on intuitionistic fuzzy soft information and Aczel-Alsina operational laws

Cited by 49 publications

References 38 publications

Application of Fuzzy-Rough Approach in Tractor Selection

Application of Fuzzy-Rough Approach in Tractor Selection

Multi-Criteria Selection of Electric Delivery Vehicles Using Fuzzy–Rough Methods

Interval-Valued Pythagorean Fuzzy Extension of DEMATEL for Prioritizing and Casualty Analysis of Environmental Criteria of Organizational Behaviour in Higher Education Sector

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