نتایج جستجو برای: z number data envelopment analysis dea
تعداد نتایج: 5243634 فیلتر نتایج به سال:
data envelopment analysis is a nonparametric technique checking efficiency of dmus using math programming. in conventional dea, it has been assumed that the status of each measure is clearly known as either input or output. kao and hwang (2008) developed a data envelopment analysis (dea) approach for measuring efficiency of decision processes which can be divided into two stages. the first stag...
Aggregating measure scores is an important step in multiple criteria decision-making, determining the overall effectiveness from dissimilar measures. One of the most popular aggregating methods is Simple Additive Weighting (SAW), which assigns weights to measures based on subjective preference information, and sum weighted scores up. The quality of overall score is highly dependent on the quali...
Data Envelopment Analysis (DEA) is the most commonly used approach for evaluating healthcare efficiency (Hollingsworth, 2008), but a long-standing concern is that DEA assumes that data are measured without error. This is quite unlikely, and DEA and other efficiency analysis techniques may yield biased efficiency estimates if it is not realized (Gajewski, Lee, Bott, Piamjariyakul and Taunton, 20...
measuring the performance of a production system has been an important task in management for purposes of control, planning, etc. lord kelvin said :“when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind.” hence, manageme...
the purpose of this paper is to offer the equitable method for ranking decision making units(dmus) based on the dynamic data envelopment analysis (ddea) concept, where quasi-fixed inputs or intermediate products are the source of inter-temporal dependence between consecutive periods. in fact, this paper originally makes the use of an approach extending the ranking of dmus in dea by khodabakhsh...
In the data envelopment analysis context, problems related to discrimination between efficient and inefficient decision-making units often arise, particularly if there are a relatively large number of variables with respect to observations. This paper presents a comparison of two discrimination-improving methods published in the literature that do not require additional preferential information...
This paper provides an application of Data Envelopment Analysis (DEA) to the measurement of the relative efficiency of highway maintenance operations within eight counties across the state of Virginia over the fiscal years 2003 to 2007. Selection of controllable and uncontrollable factors that are appropriate for the evaluation of efficiency performance is discussed. Regression Analysis, Analyt...
data envelopment analysis (dea) has been proven as an efficient technique to evaluate the performance of homogeneous decision making units (dmus) where multiple inputs and outputs exist. in the conventional applications of dea, the data are considered as specific numerical values with explicit designation of being an input or output. however, the observed values of the data are sometimes imprec...
this paper processes a combined method, based on vikor and data envelopment analysis (dea) to select the units with most efficiency. we utilize the vikor as compromise solution method. this research is a two-stage model designed to fully rank the alternatives, where each alternative has multiple inputs and outputs. the problem involves belief parameters in the solution procedure. first, the alt...
The topology of a network seriously affects its cost, reliability, throughput, and traffic pattern, etc, so we need to simultaneously consider these multiple criteria, which have different units, when evaluating network topologies. However, ordinary methods of network topology design considered only a single criterion. DEA (data envelopment analysis) enables us to simultaneously evaluate multip...
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