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Fuzzy Data Envelopment Analysis with SBM using α-level Fuzzy Approach

Author(s)
Qaiser Farooq Dar Division of International Trade Incheon National University (INU), South Korea
Ahn Young Hyo Division of International Trade Incheon National University (INU), South Korea
Gulbadian Farooq Dar Department of Statistics, Ramanujan School of Mathematical Sciencem, Pondicherry University, India
Shariq Ahmad Bhat Department of Commerce Islamic College of Science and Commerce Srinagar-India
Arif Muhammad Tali Department of Statistics Amar Singh College, Srinagar Srinagar-India
Yasir Hamid Bhat Department of Computer Science and Engineering Islamic University of Science & Technology, Kashmir-India
Abstract
In this paper, a generalized ratio-type estimator based on ranked set sampling (RSS) is proposed for The applications of fuzzy analysis in data-oriented techniques are the challenging aspect in the field of applied operational research. The use of fuzzy set theoretic measure is explored here in the context of data envelopment analysis (DEA) where we are utilizing the fuzzy a-level approach in the three types of efficiency models. Namely, BCC models, SBM model and supper efficiency model in DEA. It was observed from the result that the fuzzy SBM model has good discrimination power over fuzzy BCC. On the other side, both the models fuzzy BCC and fuzzy SBM are not able to make the genuine ranking which is acceptable for all. So this weakness is overcome with the help of fuzzy super SBM model and all three models are applied to illustrate the types of decisions and solutions that are achievable when the data are vague and prior information is in imprecise. In this paper, we are considering that our inputs and outputs are not known with absolute precision in DEA and here, we using Fuzzy-DEA models based on an a-level fuzzy approach to assessing fuzzy data.
Publication Details
Page(s) 481-501
DOI DOI not available
Published Journal: Pakistan Journal of Statistics and Operation Research, Volume: 15, Issue: 2, Year: 2019

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Keywords
Data Envelopment Analysis, Fuzzy Set, Linear Parametrical Programming, Vague, Fuzzy Equalities, and Inequalities
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