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Author: search.filters.author.Agarwal, ShiviSubject: search.filters.subject.Efficiency

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    Ranking of Efficient DMUs Using Super-Efficiency Inverse DEA Model
    (Springer, 2023-03) Mathur, Trilok; Agarwal, Shivi
    The overall potential for improving the relative efficiency of decision-making units (DMUs) is revealed by applying the data envelopment analysis (DEA) model. This study proposes a ranking system for ordering efficient DMUs with a super-efficiency inverse DEA (IDEA) model under a constant return to scale (CRS) assumption. IDEA is applied to evaluate the expected output or input variation level while keeping the efficiency value unchanged. For a numerical illustration of the proposed model in real-life problems, firstly, this study calculated the efficiency score of all 52 bus depots of Rajasthan State Road Transport Corporation (RSRTC) for the year 2018–19, applying the DEA model under the CRS assumption. The results revealed that 7 bus depots are efficient. Secondly, these 7 efficient depots have been ranked using the proposed super-efficiency IDEA model.
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    Fuzzy Slack Based Measure of Data Envelopment Analysis: A Possibility Approach
    (Springer, 2014-01) Agarwal, Shivi
    Slack based measure (SBM) model of Data Envelopment Analysis (DEA) is very effective to evaluate the relative efficiency of decision making units (DMUs). It deals with the directly input excess and output shortfall to assess the effect of slacks on efficiency with common crisp inputs and outputs. In some cases, input and output data of DMUs can’t be precisely measured, so, the uncertain theory has played an important role in DEA. In these cases, the data can be represented as linguistic variable characterized by fuzzy numbers. This paper attempts to extend the traditional DEA model to a fuzzy framework, thus proposing a fuzzy SBM DEA model based on possibility approach to deal with the efficiency measuring problem with the given fuzzy input and output data. Finally, numerical examples are presented to illustrate the proposed fuzzy SBM model. By extending to fuzzy environment, the DEA approach is made more powerful for application
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    Efficiency Measure by Fuzzy Data Envelopment Analysis Model
    (Taylor & Francis, 2018-11) Agarwal, Shivi
    Data envelopment analysis (DEA) is a non-parametric technique to measure the relative efficiencies of a set of decision making units (DMUs) with common crisp inputs and outputs. Input and output data of DMUs often fluctuate. These fluctuating data can be represented as linguistic variable characterized by fuzzy numbers. This paper attempts to extend the traditional DEA model to a fuzzy framework, thus proposing a fuzzy DEA model based on α-cut approach to deal with the efficiency measuring and ranking problem with the given fuzzy input and output data. Finally, a numerical example is presented to illustrate the fuzzy DEA model. Since the efficiency measures are expressed by membership functions rather than by crisp values, more information is provided for management. By extending to fuzzy environment, the DEA approach is made more powerful for application.