信息不确定条件下的鲁棒数据包络分析建模

为应对传统DEA方法在信息不确定条件下评价结果可能出现不稳定的现象,结合鲁棒优化方法,构建鲁棒数据包络分析RDEA模型,分别和同时应对投入产出数据受到扰动的情形,以增强DEA评价方法的可靠性.算例和敏感性分析表明RDEA方法对投入产出数据不确定性有免疫作用,通过适当牺牲最优性实现了提升效率评价结果稳定性的目的.

Robust data envelopment analysis modeling under uncertain information

Based on the robust optimization approaches,several robust data envelopment analysis (RDEA) methods are proposed in this paper so as to deal with the negative impact of uncertain information to the evaluation results of traditional DEA method.The RDEA models are implemented in a numerical example and the efficiencies and rankings of these models are compared.The evaluation and sensitivity analysis results indicate that the proposed RDEA models can be immune against inputing and outputing data uncertainties and provid more reliable and stable efficiency evaluation information.