Super-efficiency data envelopment analysis (DEA) model is obtained when a decision making unit (DMU) under evaluation is excluded from the reference set. Because of the possible infeasibility of super-efficiency DEA model, the use of super-efficiency DEA model has been restricted to the situations where constant returns to scale (CRS) are assumed. It is shown that one of the input-oriented and ...

in this study, the optimization of energy consumption and reduction of greenhouse gas emissions of irrigated lentil production in esfahan province were conducted using data envelopment analysis (dea) method. the used data were collected randomly from 140 lentil producers using a face to face questionnaire method in the cropping season of 2014-2015. based on two dea models of constant returns to...

One of the fundamental problems in the classic DEA is lack of ability to distinguish unit's performance scores that is considered as a disadvantage. Recently, Parkan et al. [9] tried to address this problem.   They proposed to assess each unit both optimistic and pessimistic views are taken into account. In contrast to traditional evaluation, one index is considered for each unit based on the l...

in data envelopment analyze (dea) the scale efficiency in the input-oriented ccr model is less than or equal to the scale efficiency in dea based on the fractional analysis (dea-r). also, the scale efficiency in case of multiple inputs and one output and vice versa the scale efficiencies are equal in dea and dea-r. in this paper, first, dea-r model with weight restrictions when there is relativ...

In many applications, discrimination among decision making units (DMUs) is a problematic technical task procedure to decision makers in data envelopment analysis (DEA). The DEA models unable to discriminate between extremely efficient DMUs. Hence, there is a growing interest in improving discrimination power in DEA yet. The aim of this paper is ranking extreme efficient DMUs in DEA based on exp...

Learning from high performance projects is crucial for software process improvement. Therefore, we need to identify outstanding projects that may serve as role models. It is common to measure productivity as an indicator of performance. It is vital that productivity measurements deal correctly with variable returns to scale and multivariate data. Software projects generally exhibit variable ret...

Data Envelopment Analysis (DEA) is used to measure the relative efficiency of the fourteen police precincts in Taipei city, Taiwan. Our results indicate how DEA may be used to measure these police precincts from commonly available police statistical data for the years 1994, 1995, and 1996. To sharpen our efficiency estimates, we use window analysis, slack variable analysis, and output-oriented ...