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Measuring performance with common weights: network DEA
(Springer, 2019-05-10)
In conventional data envelopment analysis (DEA), a production system has been seen as a black box for measuring the efficiency without any attention to what is happening inside the system. However, in practice, performance ...
A common set of weight approach using an ideal decision making unit in data envelopment analysis
(AIMS, 2012-08)
Data envelopment analysis (DEA) is a common non-parametric frontier analysis method. The multiplier framework of DEA allows flexibility in the selection of endogenous input and output weights of decision making units (DMUs) ...
Data envelopment analysis: An efficient duo linear programming approach
(2011)
Data envelopment analysis (DEA) is a powerful mathematical method that utilises linear programming (LP) to determine the relative efficiencies of a set of functionally similar decision-making units (DMUs). Evaluating the ...
The role of multiplier bounds in fuzzy data envelopment analysis
(Springer, 2017-01-30)
The non-Archimedean epsilon ε is commonly considered as a lower bound for the dual input weights and output weights in multiplier data envelopment analysis (DEA) models. The amount of ε can be effectively used to differentiate ...
Improving the computational complexity and weights dispersion in fuzzy DEA
(World Scientific Publishing Co, 2013)
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; ...
Chance-constrained cost efficiency in data envelopment analysis model with random inputs and outputs
(Springer, 2018-02-20)
Data envelopment analysis (DEA) is a well-known non-parametric technique primarily used to estimate radial efficiency under a set of mild assumptions regarding the production possibility set and the production function. ...
Allocating fixed resources and setting targets using a common-weights DEA approach
(Elsevier, 2013)
Data envelopment analysis (DEA) is a data-driven non-parametric approach for measuring the efficiency of a set of decision making units (DMUs) using multiple inputs to generate multiple outputs. Conventionally, DEA is used ...
A common-weights DEA model for centralized resource reduction and target setting
(Elsevier, 2014-11-20)
Data Envelopment Analysis (DEA) is a powerful tool for measuring the relative efficiency for a set of Decision Making Units (DMUs) that transform multiple inputs into multiple outputs. In centralized decision-making systems, ...
Positive and normative use of Fuzzy DEA-BCC models: A critical view on NATO enlargement
(Wiley, 2013)
Data envelopment analysis (DEA) is a widely used mathematical programming approach for comparing the input and output of a set of comparable decision-making units (DMUs) by evaluating their relative efficiency. The traditional ...
Imprecise data envelopment analysis for the two-stage process
(2013)
The aggregate black-box approach of conventional Data Envelopment Analysis (DEA) limits its usefulness in situations where the observation is the result of independent decision making in sub-units (sub-DMUs), sequentially ...
