Neutrosophic Data Envelopment Analysis Based on the Possibilistic Mean Approach

• Autorzy: Kshitish, Kumar Mohanta , Deena, Sunil Sharanappa , Vishnu, Narayan Mishra
• Języki publikacji: EN

Abstrakty

EN

Data envelopment analysis (DEA) is a non-parametric approach for the estimation of production frontier that is used to calculate the performance of a group of similar decision-making units (DMUs) which employ comparable inputs to produce related outputs. However, observed values might occasionally be confusing, imprecise, ambiguous, inadequate, and inconsistent in real- world applications. Thus, disregarding these factors may result in incorrect decision-making. Thus neutrosophic sets have been created as an extension of intuitionistic fuzzy sets to epresent ambiguous, erroneous, missing, and inaccurate information in real-world applications. In this study, we have proposed a technique for solving the neutrosophic form of the Charnes- Cooper-Rhodes (CCR) model based on single-value trapezoidal neutrosophic numbers (SVTrNNs). The possibilistic mean for SVTrNNs is redefined and applied the Mehar approach to transforming the neutrosophic DEA (Neu-DEA) model into its corresponding crisp DEA model. As a result, the efficiency scores of the DMUs are calculated using different risk parameter values lying in [0, 1]. A numerical example is given to analyze the performance of the all India institutes of medical sciences and compared it with Abdelfattah's ranking approach. (original abstract)

Słowa kluczowe

EN

Mathematical economic models; Mathematical analysis; Research efficiency; Effectiveness

PL

Matematyczne modele ekonomiczne; Analiza matematyczna; Badanie efektywności; Efektywność

• Czasopismo: Operations Research and Decisions
• Rocznik: 2023
• Tom: 33
• Numer: nr 2
• Strony: 81--98

Twórcy

autor

Kshitish, Kumar Mohanta

• Indira Gandhi National Tribal University, India

autor

Deena, Sunil Sharanappa

• Indira Gandhi National Tribal University, India

autor

Vishnu, Narayan Mishra

• Indira Gandhi National Tribal University, India

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Identyfikatory

DOI

10.37190/ord230205