In this paper, grey system theory and DEA are combined to establish a grey DEA model. In traditional DEA model, Input and output values of decision-making groups are all real numbers and real variables. They are replaced by grey numbers and grey variables in grey DEA model respectively. Using positioning solution method of grey linear programming, we prove the necessary condition for grey effec...

The spectroscopic and electrochemical properties of a series of four RuII polypyridyl complexes are reported. Compounds of the form [Ru(dmb)x(dea)3-x] (x ) 0-3), where dmb is 4,4′-dimethyl-2,2′-bipyridine and dea is 4,4′-bis(diethylamino)-2,2′-bipyridine, have been prepared and studied using static and time-resolved electronic and vibrational spectroscopies as a prelude to femtosecond spectrosc...

An algorithm stral:egy is proposed for use with the assurance region (AR) approach in data envelopment analysis (DEA). The strategy addressed in this study characterizes and cla.5sifies all decision making units (DMUs) into several subsets, using the revised simplex method of linear programming. Then, each DMU subset is solved by a different algorithm. Experimental studies consisting of randoml...

In many data envelopment analysis (DEA) applications, the analyst always confronts the difficulty that the selected data set is not suitable to apply traditional DEA models for their poor discrimination. This paper presents an approach using Shannon’s entropy to improve the discrimination of traditional DEA models. In this approach, DEA efficiencies are first calculated for all possible variabl...

Data envelopment analysis (DEA) has gained great popularity in environmental performance measurement because it can provide a synthetic standardized environmental performance index when pollutants are suitably incorporated into the traditional DEA framework. Past studies about the application of DEA to environmental performance measurement often follow the concept of radial efficiency measures....

Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative efficiency of decision making units (DMUs) on the basis of multiple inputs and outputs. The context-dependent DEA is introduced to measure the relative attractiveness of a particular DMU when compared to others. In real-world situation, because of incomplete or non-obtainable information, the data (Input and ...

Data Envelopment Analysis (DEA) is computationally intensive. This work answers conclusively questions about computational performance and scale limits of the standard LP-based procedures currently used. Examples of DEA problems with up to 15K entities are documented and it is not hard to imagine problem size increasing as new more sophisticated applications are found for DEA. This work reports...