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; ...

In a recent paper, Jiménez et al. (2007) propose a ‘general’ and ‘interactive’ method for solving linear programming problems with fuzzy parameters. In this study, we propose a revision to the optimal crisp value of the ...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. In the conventional DEA, all the data ...

Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These ...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are ...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are ...

The linear programming technique for multidimensional analysis of preference (LINMAP) as a multi-attribute decision-making (MADM) technique has a capability of determining the weights of attributes as well as providing a ...