‎in this paper, we present a two-stage model for ranking of decision making units (dmus) using interval analytic hierarchy process (ahp). since the efficiency score of unity is assigned to the efficient units, we evaluate the efficiency of each dmu by basic dea models and calculate the weights of the criteria using proposed model. in the first stage, the proposed model evaluates decision making...

in the present study, an attempt has been made to use data envelopment analysis (dea) for assessing the technical efficiency and return-to-scale for greenhouse cucumber production in iran. for this purpose, the data from greenhouses in esfahan province, during one period of plant cultivation in one year including spring plants were randomly collected. the results indicated that total input ener...

background: one way to improve the performance of hospitals, the largest resource-consuming units in the healthcare sector, is to continuously evaluate their performance.objective: the current study assessed the performance of hospitals affiliated with the kurdistan university of medical sciences using data envelopment analysis (dea).methods: this retrospective descriptive-analytic study used d...

background: nowadays, healthcare systems are considered as important service sectors, and they are social development and welfare standards; hence the performance of this sector is highly important. evaluating performance is the first step of various departments to determine the efficiency of the healthcare system. in the meantime, diagnostic laboratories of hospitals play important roles as sp...

Data Envelopment Analysis (DEA) is a nonparametric approach for measuring the relative efficiency of a decision making units consists of multiple inputs and outputs. In all standard DEA models semi positive real valued measures are assumed, while in some real cases inputs and outputs may take complex valued. The question is related to measuring efficiency in such cases. As far as we are aware, ...

this paper introduces discretionary imprecise data in data envelopment analysis (dea) and discusses the efficiency evaluation of decision making units (dmus) with non-discretionary imprecise data. then, suggests a method for evaluation the efficiency of dmus with non-discretionary imprecise data. when some inputs and outputs are imprecise and non-discretionary, the dea model becomes non-linear ...

Data Envelopment Analysis (DEA) provides means for piecewise linear approximation of production functions. To improve the fit to the data we propose to improve the flexibility of the frontier by extending DEA towards a more general piecewise quadratic approximation, called Quadratic Data Envelopment Analysis (QDEA). In contrast to the linear approximation, the quadratic approximation allows for...

a new algorithm for classification of dmus to efficient and inefficient units in data envelopment analysis is presented. this algorithm uses the non-archimedean charnes-cooper-rhodes[1] (ccr) model. also, it applies an assurance value for the non-archimedean                          using only simple computations on inputs and outputs of dmus (see [18]). the convergence and efficiency of the ne...