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Multiobjective Target Setting In Data Envelopment Analysis Using Ahp

机译:使用Ahp进行数据包络分析的多目标目标设置

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In this paper two new target setting DEA approaches are proposed. The first one is an interactive multiobjective method that at each step of the process asks the decision maker (DM) which inputs and outputs he wishes to improve, which ones are allowed to worsen and which ones should stay at their current level. The local relative priorities of these inputs and outputs changes are computed using the analytic hierarchy process (AHP). After obtaining the candidate target, the DM can update his preferences for improving, worsening or maintaining current inputs and outputs levels and obtain a new candidate target. Thus continuing, until a satisfactory operating point is computed. The second method proposed uses a lexicographic multiobjective approach in which the DM specifies a priori a set of priority levels and, using AHP, the relative importance given to the improvements of the inputs and outputs at each priority level. This second approach requires solving a series of models in order, one model for each priority level. The models do not allow for worsening of neither inputs nor outputs. After the lowest priority model has been solved the corresponding target operating point is obtained. The application of the proposed approach to a port logistics problem is presented.
机译:本文提出了两种新的目标设定DEA方法。第一个是交互式多目标方法,在过程的每个步骤中,决策者都会询问决策者(DM)他希望改善的输入和输出,哪些恶化,哪些保持在当前水平。这些输入和输出更改的本地相对优先级是使用层次分析法(AHP)计算的。在获得候选目标之后,DM可以更新其用于改善,恶化或保持当前输入和输出水平的偏好,并获得新的候选目标。因此继续进行,直到计算出令人满意的工作点为止。提出的第二种方法使用词典编目多目标方法,其中DM先验指定一组优先级,并使用AHP来确定在每个优先级上改进输入和输出的相对重要性。第二种方法要求按顺序求解一系列模型,每个优先级对应一个模型。该模型不允许输入或输出都恶化。解决最低优先级模型后,即可获得相应的目标工作点。介绍了该方法在港口物流中的应用。

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