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首页> 外文期刊>International journal of productivity and quality management >Performance evaluation of production companies using data envelopment analysis and Monte Carlo simulation: a case study
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Performance evaluation of production companies using data envelopment analysis and Monte Carlo simulation: a case study

机译：使用数据包络分析和蒙特卡洛模拟的生产公司绩效评估：一个案例研究

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摘要

Data envelopment analysis based on linear programming model, is a scientific approach, which evaluates the efficiency of organisations and units which use multiple inputs in order to produce multiple outputs. Data envelopment analysis models presented by Charnes, Cooper and Rhodes have intentional deficiencies, one of which is relying on data from periods of time that decision making units have passed. Therefore the results are based on past data. This is especially significant when the goal is to evaluate the current efficiency of units and forecast their future performance. On the other hand, classic DEA modes, such as BCC and CCR are based on the assumption that the precise and definite numerical value of all inputs and outputs are in hand, while in real world this is not always the case; specifically when the decision maker intends to evaluate the performance in long period of time in which values are definitively imprecise and inputs and outputs come as time series. The purpose of this article is to present an approach composing of DEA and Monte Carlo simulation which enables the decision maker to find the most efficient organisation in a given period of time, considering imprecise time series of data and also helps with forecasting and estimating the efficiency of companies in the future for a safe investment.
机译：基于线性规划模型的数据包络分析是一种科学的方法，它评估使用多个输入以产生多个输出的组织和单位的效率。 Charnes，Cooper和Rhodes提出的数据包络分析模型存在故意缺陷，其中之一是依赖决策部门经过一段时间的数据。因此，结果基于过去的数据。当目标是评估设备的当前效率并预测其未来性能时，这一点尤其重要。另一方面，经典的DEA模式（例如BCC和CCR）基于所有输入和输出的精确和确定的数值都在手的假设，而在现实世界中，情况并非总是如此。尤其是当决策者打算在很长时间内评估性能时，其中值肯定是不精确的，输入和输出随时间序列变化。本文的目的是提出一种由DEA和蒙特卡洛模拟组成的方法，该方法使决策者可以在给定的时间段内找到最有效的组织，同时考虑不精确的数据时间序列，还有助于预测和评估效率未来的公司进行安全投资。

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