Issue: 2023/Vol.33/No.2, Pages 81-98
NEUTROSOPHIC DATA ENVELOPMENT ANALYSIS BASED ON THE POSSIBILISTIC MEAN APPROACH
Kshitish Kumar Mohanta
, Deena Sunil Sharanappa , Vishnu Narayan Mishra
Cite as: K. K. Mohanta, D. S. Sharanappa, V. N. Mishra. Neutrosophic data envelopment analysis based on the possibilistic mean approach. Operations Research and Decisions 2023: 33(2), 81-98. DOI 10.37190/ord230205
Abstract
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.
Keywords: efficiency analysis, single value, trapezoidal neutrosophic number, data envelopment analysis, possibilistic mean, mehar approach
Received: 28 July 2022 Accepted: 14 March 2023
Published online: 24 June 2023