Now showing items 1-6 of 6
Evaluating the performance and ranking of DMUs: A fuzzy bounded DEA approach
Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. Unfortunately, the existing DEA models are ...
An overall profit Malmquist productivity index with fuzzy and interval data
Although crisp data are fundamentally indispensable for determining the profit Malmquist productivity index (MPI), the observed values in real-world problems are often imprecise or vague. These imprecise or vague data can ...
A bounded data envelopment analysis model in a fuzzy environment with an application to safety in the semiconductor industry
Data envelopment analysis (DEA) is a mathematical programming approach for evaluating the relative efficiency of decision making units (DMUs) in organizations. The conventional DEA methods require accurate measurement of ...
A robust optimization approach for imprecise data envelopment analysis
Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA). However, the input and output data in real-world problems are often imprecise or ambiguous. Some researchers have ...
Data envelopment analysis with fuzzy parameters: An interactive approach
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 ...
A flexible cross-efficiency fuzzy data envelopment analysis model for sustainable sourcing
Sustainable sourcing is a recent priority for firms considering customer behavior and societal norms with respect to the supply chain. Customer attitudes, particularly in the developed countries, are affected by the perceived ...