Recently the concept of facility efficiency, which defined by data envelopment analysis (DEA), introduced as a location modeling objective, that provides facilities location’s effect on their performance in serving demands. By combining the DEA models with the location problem, two types of “efficiencies” are optimized: spatial efficiency which measured by finding the least cost location and al...

data envelopment analysis (dea) is a technique used to compare efficiency in various sectors such as hospitals, chain stores, and dealerships. it represents a set of linear programming techniques and uses deter-ministic data (inputs and outputs), in stable conditions. the dea technique cannot be used when there is data with indeterministic nature, or when there is an environment with dynamic co...

In performance evaluations, data without explicit inputs (such as index data, pure output data) are widely used. To directly use such data, this paper presents a study on building DEA models without explicit inputs,DEA-WEI models, in which convexity assumption is considered to be satisfied while the ratio data are constructed. Finally, an example of the modified DEA-WEI model is presented and c...

Data Envelopment Analysis is based on linear programming problems (LPP) in order to find the efficiency of Decision Making Units (DMUs). This process can be computationally intense, as a LPP has to be run for each unit. Besides, a typical DEA LPP has a large number of redundant constraints concerning the inefficient DMUs. That results in degenerate LPPs and in some cases, multiple efficient sol...

In this paper, we re-examine Data Envelopment Analysis models from perspectives of preference order, production set and performance measure. we investigate the relationship between Data Envelopment Analysis (DEA) and Multiple Criteria Decision Making Theory. There are three key building blocks in a DEA model: preference order, production possibility set and performance measure. It is shown in t...

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...

data envelopment analysis (dea) is a mathematical programming method in operations research that can be used to distinguish between efficient and inefficient decision making units (dmus). however, the conventional dea models do not have the ability to rank the efficient dmus. this article suggests bootstrapping method for ranking measures of technical efficiency as calculated via non-radial mod...

the non-differentiability and implicit definition of boundary of production possibility set (pps) in data envelopment analysis (dea) are two important difficulties for obtaining directional characteristics, including different elasticity measures and marginal rates of substitution. also, imposing weight restrictions in dea models have some shortcomings and misunderstandings. in this paper we ut...

data envelopment analysis (dea) models with interval inputs and outputs have been rarely discussed in dea literature. this paper, using the enhanced russell measurement proposes an extended model which permits the presence of interval scale variables which can take both negative and positive values. the model is compared with most well-known dea models of which include the ccr model, the bcc mo...