Fuzzy Data Envelopment Analysis Models with R Codes
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The conventional DEA models such as CCR and BBC models require precise input and output data, which may not always be available in real world applications. However, in real life problems, inputs and outputs are often imprecise. To deal with imprecise data, the notion of fuzziness has been introduced in DEA and so the DEA has been extended to fuzzy DEA (FDEA). In this chapter, the main approaches for solving FDEA models are classified into five groups and the mathematical approaches of each category are described briefly. Then, R codes for each FDEA model are provided. Finally, numerical examples are provided to illustrate the main advantages of R in FDEA models.
KeywordsData envelopment analysis Fuzzy numbers Fuzzy ranking Possibility measure Fuzzy arithmetic R code
- 9.Hatami-Marbini, A., Tavana, M., Emrouznejad, A., Saati, S.: Efficiency measurement in fuzzy additive data envelopment analysis. Int. J. Ind. Syst. Eng. 10(1), 1–20 (2012)Google Scholar
- 33.Bhardwaj, B., Kaur, J., Kumar, A.: A new fuzzy CCR data envelopment analysis model and its application to manufacturing enterprises. In: Collan, M., Kacprzyk, J. (eds.) Soft Computing Applications for Group Decision-making and Consensus Modeling. Studies in Fuzziness and Soft Computing, vol. 357. Springer, Cham (2018)Google Scholar