نتایج جستجو برای: inputs and outputs
تعداد نتایج: 16830957 فیلتر نتایج به سال:
Data envelopment analysis (DEA) has been proved to be an excellent approach for measuring the performance of decision-making units (DMUs) that use multiple inputs to generate multiple outputs. But the allocation problem of shared inputs and undesirable outputs does not arouse attention in this movement. This paper proposes a two-stage DEA model considering simultaneously the structure of shared...
In this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (DMUs) in stochastic data envelopment analysis (DEA) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. It is shown that this deterministic model can be converted to a quadratic programming model. So fa...
data envelopment analysis (dea) is a non-parametric approach for performance analysis of decision making units (dmus) which uses a set of inputs to produce a set of outputs without the need to consider internal operations of each unit. in recent years, there have been various studies dealt with two-stage production systems, i.e. systems which consume some inputs in their first stage to produce ...
data envelopment analysis (dea) is a method for measuring the efficiency of peer decision making units (dmus) which uses a set of inputs to produce a set of outputs. in some cases, dmus have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. one important issue in two-stage dea is the sensitivity of...
In the real world applications, there are some situations where inputs and outputs are time-dependent and are affected during the production periods. Capital stock can be seen as an effective instance in such occasions. In order to handling long-time planning, dynamic structure was proposed in efficiency evaluation. In this framework, there are some of the inputs and outputs change proportiona...
Traditional DEA models do not deal with imprecise data and assume that the data for all inputs and outputs are known exactly. Inverse DEA models can be used to estimate inputs for a DMU when some or all outputs and efficiency level of this DMU are increased or preserved. this paper studies the inverse DEA for fuzzy data. This paper proposes generalized inverse DEA in fuzzy data envelopment anal...
Data envelopment analysis (DEA) is a method to measure relative efficiency of a set of decision-making units (DMUs) which uses multiple inputs and produces multiple outputs. In the conventional DEA, crisp inputs and outputs are fundamentally necessary. But the observed values of inputs and outputs in real-world problems are sometimes imprecise. Thus, performance measurement often needs to be do...
Traditional data envelopment analysis (DEA) models deal with measurement of relative efficiency of decision making units (DMUs) in which multiple-inputs consumed to produce multiple-outputs. One of the drawbacks of these models is neglecting internal processes of each system, which may have intermediate products and/or independent inputs and/or outputs. In this paper some methods which are usab...
in this paper, we consider the production possibility set with n production units such that the following four principles that governs: inclusion observations, conceivability, immensity and convexity. our goal is to estimate the output of a same and new production unit with existing production possibility and amount of input is specified. so, initially we find the interval changes of each input...
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