فهرس المقالات Effi

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  1 - Review of the methods for evaluating congestion in DEA and computing output losses due to congestion
  H. Zare Haghighi M. Khodabakhshi G. R. Jahanshahloo
  Data Envelopment Analysis (DEA) is a branch of management, concerned with evaluating the performances of homogeneous Decision Making Units (DMUs). The performances of DMUs are affected by the amount of sources that DMUs used. Usually increases in inputs cause increases أکثر

  Data Envelopment Analysis (DEA) is a branch of management, concerned with evaluating the performances of homogeneous Decision Making Units (DMUs). The performances of DMUs are affected by the amount of sources that DMUs used. Usually increases in inputs cause increases in outputs. However, there are situations where increase in one or more inputs generate a reduction in one or more outputs. In such situations there is congestion in inputs or production process. In this study, we review the approaches that are available in the DEA literature for evaluating congestion. Also we introduce a model to compute output losses due to congestion. Then, we present the results of the mentioned models on an empirical example and interpret the results. تفاصيل المقالة
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  2 - On the relative efficiency in general network structures
  F. Boloori J. Pourmahmoud Gazijahani
  Data Envelopment Analysis (DEA) is an eciency measurement tool for evaluation of similar Decision Making Units (DMUs). In DEA, weights are assigned to inputs and outputs and the absolute eciency score is obtained by the ratio of weighted sum of outputs to weighted sum أکثر

  Data Envelopment Analysis (DEA) is an eciency measurement tool for evaluation of similar Decision Making Units (DMUs). In DEA, weights are assigned to inputs and outputs and the absolute eciency score is obtained by the ratio of weighted sum of outputs to weighted sum of inputs. In traditional DEA models, this measure is also equivalent with relative eciency score which evaluates DMUs in compare with the most ecient DMU. Recently network DEA models are appeared in the literature, which try to assess DMUs regarding their internal production divisions and intermediate products. In this paper we compare absolute and relative eciency scores in network framework. Since in network DEA models, an ecient DMU does not exist necessarily, the relative eciency model helps us to have at least one ecient DMU in our assessments. تفاصيل المقالة
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  3 - Groups performance ranking based on inefficiency sharing
  M. Momeni G. R. Jahanshahloo M. Rostamy Malkhalifeh S. Razavi K. Yakideh
  In the real world there are groups which composed of independent units. The conventional data envelopment analysis(DEA) model treats groups as units, ignoring the operation of individual units within each group.The current paper, investigates parallel system network app أکثر

  In the real world there are groups which composed of independent units. The conventional data envelopment analysis(DEA) model treats groups as units, ignoring the operation of individual units within each group.The current paper, investigates parallel system network approach proposed by Kao and modifies it. As modied Kao' model is more eligible to recognize ecient groups, a new ranking method is proposed based on a model which calculates eciencies with additional constraint that made model share constant ineciency among groups.To show advantages, modies model is applied to eciency calculation of both articial and real groups and results is compared with conventional DEA model and parallel system network model as well.Finally it is shown by tow numerical and empirical examples that ecient groups recognized by modied model how can be ranked according to proposed ranking model. تفاصيل المقالة