Improving the computational complexity and weights dispersion in fuzzy DEA
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.
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
Research Institute : Centre for Enterprise and Innovation (CEI)