Data envelopment analysis (DEA) has been widely applied in evaluating multicriteria decision making problems, which have multi-input and multi-output. However, the traditional DEA method does neither take the decision maker’s subjective preferences to the individual criteria into consideration nor rank the selected options or decision making units (DMUs). On the other hand, Satty’s analytical h...

In this paper we first (trivially) show that data envelopment analysis can be viewed as maximising the sum of the efficiencies of the decision-making units (DMU's) in the organisation. Building upon this we present nonlinear models for: (a) allocating fixed costs to DMU's and (b) allocating resources to DMU's. Simultaneous to allocating resources output targets are also decided for each DMU. Nu...

Atrazine (ATR), hydroxyatrazine (OH-ATR), and the three chloro metabolites of ATR (deethylatrazine [DEA], deisopropylatrazine [DIA], diaminochlorotriazine [DACT]) were evaluated for developmental effects in rats and rabbits. Three developmental toxicity studies were conducted on ATR in rats (two studies) and rabbits and a developmental toxicity study was conducted in rats for each of the four A...

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) is a wide range of mathematical models that used for measuring the relative efficiency of a set of harmonic units whit similar inputs and outputs. this model calculates some different weight for input and output variables in each decision making model. this variation in similar weights caused some critiques to this method. from 1991 some linear and nonlinear mode...

Traditional DEA method is improper for supplier evaluation and selection, as it adopts varying weights in evaluation, and fails to consider competition among the suppliers. In order to solve these two problems, Nash bargaining game DEA model is applied to supplier evaluation in present paper. However, there is a non-uniqueness problem with Nash bargaining game efficiency of supplier in existing...

Data envelopment analysis (DEA) is a performance measurement tool that was initially developed without consideration of the decision maker (DM)’s preference structures. Ever since, there has been a wide literature incorporating DEA with value judgements such as the goal and target setting models. However, most of these models require prior judgements on target or weight setting. This paper will...

Data Envelopment Analysis (DEA) cannot provide adequate discrimination among efficient decision making units (DMUs). To discriminate these efficient DMUs is an interesting research subject. The purpose of this paper is to present a Cross-Efficiency Profiling (CEP) model which can be used to improve discrimination power of DEA and conduct a methodological comparison of CEP and the other develope...

Return-To-Scale (RTS) is a most important topic in DEA. Many methods are not obtained for estimating RTS in DEA, yet. In this paper has developed the Banker-Trall approach to identify situation for RTS for the BCC model "multiplier form" with virtual weight restrictions that are imposed to model by DM judgments. Imposing weight restrictions to DEA models often has created problem of infeasibili...