Evaluation of Metaverse integration of freight fluidity measurement alternatives using fuzzy Dombi EDAS model

Deveci, Muhammet; Gökaşar, Ilgın; Castillo, Oscar; Daim, Tuğrul U.

doi:10.1016/j.cie.2022.108773

Cited by 58 publications

(12 citation statements)

References 34 publications

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“…Compared to many other decision-making techniques, EDAS is simpler, follows a clear logic that is easy for practitioners to understand, and the mathematical process is relatively basic. Integration of EDAS and Pythagorean fuzzy sets (PF-EDAS) is a recently developed approach that has swiftly attracted attention, having been applied in different fields, including car selection [55], sustainable circular supplier selection in the manufacturing sector [56], evaluating investment projects for highways [57] selecting an optimal drug to treat the Coronavirus ailment [58], supplier selection for coal thermal power plant [59], ship navigation environment safety assessment [60], selection of waste management techniques [61], loan evaluation for banking customers [62], analysis of metaverse integration of freight fluidity assessment solutions [63], evaluation of alternatives for mobility sharing [64] and ranking of use cases for energy blockchain [65].…”

Section: Literature Reviewmentioning

confidence: 99%

Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS

et al. 2023

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For many different types of businesses, additive manufacturing has great potential for new product and process development in many different types of businesses including automotive industry. On the other hand, there are a variety of additive manufacturing alternatives available today, each with its own unique characteristics, and selecting the most suitable one has become a necessity for relevant bodies. The evaluation of additive manufacturing alternatives can be viewed as an uncertain multi-criteria decision-making (MCDM) problem due to the potential number of criteria and candidates as well as the inherent subjectivity of various decision-experts engaging in the process. Pythagorean fuzzy sets are an extension of intuitionistic fuzzy sets that are effective in handling ambiguity and uncertainty in decision-making. This study offers an integrated fuzzy MCDM approach based on Pythagorean fuzzy sets for assessing additive manufacturing alternatives for the automotive industry. Objective significance levels of criteria are determined using the Criteria Importance Through Inter-criteria Correlation (CRITIC) technique, and additive manufacturing alternatives are prioritized using the Evaluation based on Distance from Average Solution (EDAS) method. A sensitivity analysis is performed to examine the variations against varying criterion and decision-maker weights. Moreover, a comparative analysis is conducted to validate the acquired findings.

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Section: Literature Reviewmentioning

confidence: 99%

Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS

et al. 2023

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“…Rough Dombi Bonferroni MARCOS, Rough Dombi LMAW Application in logistics (Pamučar et al, 2021a). LMAW Evaluation of Metaverse integration of freight fluidity measurement alternatives (Deveci et al, 2022).…”

Section: Application and Referencementioning

confidence: 99%

Development of the MCDM fuzzy LMAW-grey MARCOS model for selection of a dump truck

Tešić¹,

Božanić²,

Puška³

et al. 2023

Rep. Mech. Eng.

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This study presents the MCDM model created for the selection of a dump truck for the needs of the army engineering units, based primarily on the truck’s construction features and purchasing and maintenance costs. In this study was used the Methodology of Additive Weights (LMAW) in Fuzzy surrounding for determination of weight coefficients of criteria, while for the selection of the optimal alternative (for a dump truck) it was used the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method, modified by interval grey numbers. Input data for this methodology were obtained by engaging experts. Finally, the analysis was made of the sensitivity of output results of the proposed MCDM methodology to the change of weight coefficients of criteria, as well as the comparison of the obtained results with the results of other methodologies. In the conclusion, the proposed model showed stability but it was sensitive to weight coefficients change which should be taken into account by defining the same by experts.

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“…Evaluation of multiple criteria to make an optimal decision is called multi-criteria decision-making (MCDM) (Haseli et al, 2020;Torkayesh et al, 2022a;Ma et al, 2022). The aim of decision making is to select and evaluate the best option based on different criteria Deveci et al, 2022b).…”

Section: Introductionmentioning

confidence: 99%

Sustainable resilient supplier selection for IoT implementation based on the integrated BWM and TRUST under spherical fuzzy sets

Bonab

Haseli

Rajabzadeh

et al. 2023

Decis. Mak. Appl. Manag. Eng.

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Supplier selection process plays a vital role in supply chain management and is the most important variable in its success. With increasing environmental considerations, organizations must consider sustainability considerations and economic goals to protect the environment. Furthermore, the destructive effects of disruptions on the supply chain performance of companies have prompted organizational experts to pay special attention to the concept of resilience. This study developed an integrated approach based on the extended version of Multi-Criteria Decision-Making (MCDM) methods in a spherical fuzzy (SFS) environment to address sustainable and resilient IoT supplier selection. In the proposed approach, the main criteria (i.e., resilience, and sustainability) have been used in the supplier selection process. Then, these criteria are weighted using the developed SFS-Best-Worst Method (BWM), which reduces uncertainty in pairwise comparisons. In the next step, the 14 selected IoT suppliers are evaluated and prioritized by applying SFS-mulTi-noRmalization mUlti-Distance aSsessmenT (TRUST) that considers a multi-normalization algorithm to reduce subjectivity in normalized data. The results of this study shows that the pollution control and risk-taking sub-criteria are placed in the first and second priorities, respectively. The comparison of the results of the SFS-TRUST with other MCDM methods and sensitivity analysis demonstrates the performance of the proposed approach and its ranking stability in various scenarios.

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Evaluation of Metaverse integration of freight fluidity measurement alternatives using fuzzy Dombi EDAS model

Cited by 58 publications

References 34 publications

Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS

Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS

Development of the MCDM fuzzy LMAW-grey MARCOS model for selection of a dump truck

Sustainable resilient supplier selection for IoT implementation based on the integrated BWM and TRUST under spherical fuzzy sets

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