data envelopment analysis (dea) with considering the best condition for each decision making unit (dmu) assesses the relative efficiency for it and divides a homogenous group of dmus in to two categories: efficient and inefficient, but traditional dea models can not rank efficient dmus. although some models were introduced for ranking efficient dmus, franklin lio & hsuan peng (2008), proposed a...

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In models of data envelopment analysis (DEA), an optimal set of weights is generally assumed to represent the assessed decision making unit (DMU) in the best light in comparison to all the other DMUs, and so there is an optimal set of weights corresponding to each DMU. The present paper, proposes a three stage method to determine one common set of weights for decision making units. Then, we use...

Mixed models are widely used to analyze longitudinal data. In their conventional formulation as linear mixed models (LMMs) and generalized LMMs (GLMMs), a commonly indispensable assumption in settings involving longitudinal non-Gaussian data is that the longitudinal observations from subjects are conditionally independent, given subject-specific random effects. Although conventional Gaussian...

data envelopment analysis (dea) is a mathematical programming-based approach for evaluates the relative efficiency of a set of dmus (decision making units). the relative efficiency of a dmu is the result of comparing the inputs and outputs of the dmu and those of other dmus in the pps (production possibility set). also, in data envelopment analysis various models have been developed in order to...

‎In this paper allocating a fixed resource for producing ‎finite projects in order to obtaining a desired level of‎ ‎efficiency will be discussed‎. ‎Note that it is assumed that a ‎vector of limited sources is at hand‎. ‎This vector of resources can‎ ‎be contained human resource‎, ‎budget‎, ‎equipment‎, ‎and facilities‎. ‎In ‎any firm there exist different suggestions from subunits for ‎running...