The data envelopment analysis (DEA) model is an efficiency based on linear programming, which can evaluate the comprehensive of multi-input and multi-output systems. In college physical education classes, to cultivate students' exercise habits, improve classroom efficiency, promote continuous development lifelong ability, teachers must implement effective teaching methods in process. This goal ...

A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DMUs) to select the most advantageous weights in calculating their efficiency scores. This flexibility, on the other hand, deters the comparison among DMUs on a common base. For dealing with this difficulty and assessing all the DMUs on the same scale, this paper proposes using a multiple objective...

in models of data envelopment analysis (dea), an optimal set of weights is generally assumed to represent the assessed decision making unit (dmu) in the best light in comparison to all the other dmus, and so there is an optimal set of weights corresponding to each dmu. the present paper, proposes a three stage method to determine one common set of weights for decision making units. then, we use...

in this paper, presenting two simple methods for ranking of efficient dmus in dea models that included to add one virtual dmu as ideal dmu and is using the additive model. note that, we use an ideal point just for comparing efficient dmus with. although these methods are simple, they have ability for ranking all efficient dmus, extreme points and the others, also they are capable of ranking the...

in the classical data envelopment analysis (dea) models, inputs and outputs are assumed as known variables, and these models cannot deal with unknown amounts of variables directly. in recent years, there are few researches on handling missing data. this paper suggests a new interval based approach to apply missing data, which is the modified version of kousmanen (2009) approach. first, the prop...

this paper proposes an alternative approach for efficiency analysis when a set of dmus uses interval scale variables in the productive process. to test the influence of these variables, we present a general approach of deriving dea models to deal with the variables. we investigate a number of performance measures with unrestricted-in-sign interval and/or interval scale variables.

abstract. data envelopment analysis (dea) is now widely utilized as a method for assessing relative efficiency of a set of decision making units (dmus). along as evaluating relative efficiency dea models are capable of to be improved for finding benchmark for inefficient units which can help managers for better making decision. thus it is important to obtain accurate results from dea models. in...

the efficiency measurement is a subject of great interest. the majority of studies on dea models have been carried out using radial or non-radial approaches regarding the application of dea for the efficiency measurement. this paper, based on the directional distance function, proposes a new generalized hybrid measure of efficiency under generalized returns to scale with the existence of both r...

in many applications, ranking of decision making units (dmus) is a problematic technical task procedure to decision makers in data envelopment analysis (dea), especially when there are extremely efficient dmus. in such cases, many dea models may usually get the same efficiency score for different dmus. hence, there is a growing interest in ranking techniques yet. the purpose of this paper is ra...