The non-radial DEA models [1] possess some specific features. First, multiple reference sets may exist for a production unit. Second, multiple supporting hyperplanes may occur on optimal units of the frontier. Third, multiple projections (a projection set) may occur in the space of input and output variables. All these features cause certain difficulties under measurement of returns to scale of...

DEA (Deta Envelopment Analysis) is a non-parametric technique for measuring the efficiency of DMUs (Decision Making Units)with common inputs and outputs [2,5]. viewpoint for each DMU because of taking a maximum ratio. During recent years, the issue of sensitivity and stability of data envelopment analysis results has been extensively studied. The first DEA sensitivity analysis paper by Charnes ...

Data envelopment analysis technique which is developed based on the mathematical programming, evaluates the relative efficiency of a set of homogeneous decision making units. This paper shows the method of Discriminant Analysis (DA), on Imprecise Data by Data Envelopment 724 F. Hosseinzadeh Lotfi et al Analysis (DEA). DEA-Discriminant Analysis (DEA-DA) is designed to identify the existence or n...

To address the gap in energy performance studies regarding role of information entropy feedback processes between input and output slacks, paper develops a novel Stochastic-Entropic Analysis for Ideal Solutions (SEA-IS) model. The non-linear stochastic optimization model is then applied to assess potential gains that may arise from slacks minimization given different optimal reduction quantiles...

This paper develops a method based on data envelopment analysis (DEA) for efficiency assessments taking into account the effect of non-discretionary factors. A typology that classifies the non-discretionary factors into two groups is proposed: the factors that characterize the external conditions where the decision making units (DMUs) operate (external factors), and the factors that are interna...

This paper gives a new application of DEA to evaluate the scheduling solutions of parallel processing. It evaluates the scheduling solutions of parallel processing using the non-convex DEA model, FDH model. By introducing each solution of parallel processing scheduling as a DMU with some relevant inputs and outputs this paper shows that how the most efficient schedule(s) can be identified.

Supply chain performance evaluation problems are complex problems with multiple criteria and multi-layered internal linking activities. Data Envelopment Analysis (DEA) has been used to evaluate the relative performance of organizational units called Decision Making Units (DMUs). However, the conventional DEA models cannot take into account the complex nature of supply chains with internal linki...

multi-objective optimization is the simultaneous consideration of two or more objective functions that are completely or partially inconflict with each other. the optimality of such optimizations is largely defined through the pareto optimality. multiple objective integer linear programs (moilp) are special cases of multiple criteria decision making problems. numerous algorithms have been desig...

This study introduces a revised data envelopment analysis (DEA) model to explore a new use of DEA for the environmental assessment in which outputs are classified into desirable (good) and undesirable (bad). Such an output separation is important in the DEA-based environmental assessment. We used a Range-Adjusted Measure (RAM) DEA model that is a kind of non-radial DEA model for combining the t...

Super eciency data envelopment analysis(DEA) model can be used in ranking the performanceof ecient decision making units(DMUs). In DEA, non-extreme ecient unitshave a super eciency score one and the existing super eciency DEA models do notprovide a complete ranking about these units. In this paper, we will propose a methodfor ranking the performance of the extreme and non-extreme ecient units.