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    Improving the computational complexity and weights dispersion in fuzzy DEA

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    Date
    2013
    Author
    Saati, S.;
    Hatami-Marbini, A.
    Metadata
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    Abstract
    One of the prominent features of standard and fuzzy data envelopment analysis (DEA) is the representation of each of the participating decision making units (DMUs) in the best possible light. This causes two problems; first, the different set of factor weights with large number of zeros and second a large number of linear programming models to solve. In this paper, we propose an efficient method to address these two problems. In proposed method by solving just one linear programming a Common Set of Weights (CSW) is achieved in fuzzy DEA. Since resulted efficiencies by the proposed CSW are interval numbers rather than crisp values, it is more informative for decision maker. The proposed model is applied to a numerical example to demonstrate the concept.
    Description
    Citation : Saati, S. and Hatami-Marbini, A. (2013) Improving the computational complexity and weights dispersion in fuzzy DEA. Uncertainty Modeling in Knowledge Engineering and Decision Making: pp. 1070-1075
    URI
    http://hdl.handle.net/2086/13534
    DOI
    http://dx.doi.org/10.1142/9789814417747_0171
    Research Institute : Centre for Enterprise and Innovation (CEI)
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    • Department of Management and Entrepreneurship [641]

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