讲座题目： DEA-based fixed cost allocation in two-stage systems:leader-follower and satisfaction degree bargaining game approaches
报告人：储军飞
报告时间：2018年10月15日(周一)上午9:30–11:00
报告地点：经管院C373
主办单位：管理科学与工程系
报告内容摘要：
Cross-efficiency evaluation, as an extension tool of data envelopment analysis (DEA), has been widely applied in evaluating and ranking decision making units (DMUs). Unfortunately, the cross-efficiency scores generated may not be Pareto optimal, which has reduced the effectiveness of this method. To solve this problem, we propose a cross-efficiency evaluation approach based on Pareto improvement, which contains two models (Pareto optimality estimation model and cross-efficiency Pareto improvement model) and an algorithm. The Pareto optimality estimation model is used to estimate whether the given set of cross-efficiency scores are Pareto-optimal solutions. If these cross-efficiency scores are not Pareto optimal, the Pareto improvement model is then used to make cross-efficiency Pareto improvement for all the DMUs. In contrast to other cross-efficiency approaches, our approach always obtains a set of Pareto-optimal cross efficiencies under the predetermined weight selection principles for these DMUs. In addition, if the proposed algorithm terminates at its step 3, the evaluation results generated by our approach unify self-evaluation, peer-evaluation, and common-weight-evaluation in DEA cross-efficiency evaluation. Specifically, the self-evaluated efficiency and the peer-evaluated efficiency converge to the same common-weight-evaluated efficiency when the algorithm stops. This will make the evaluation results more likely to be accepted by all the DMUs.
报告人简介：
储军飞，男，1990年07月生于安徽安庆。目前为由法国巴黎萨克雷大学与中国科学技术大学联合培养双学位博士在读(分别预计为2018年12月底和10月底毕业)。主要研究方向为基于数据包络分析的交叉效率评价、能源环境绩效评价、资源分配、固定成本分摊等。目前已在European Journal of Operational Research, International Journal of Production Research, Journal of the operational Research Society等国际知名SCI/SSCI期刊发表20余篇(一半以上为其一作、通讯或除导师外一作)。现任10几个国际知名学术期刊的审稿人。曾获得研究生国家奖学金(三次)、中科院院长奖学金、中科院朱李月华奖学金等荣誉。
