Dual frontiers without convexity

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• 作者：Abdullah Aldamak^a ; ^b ; ^{abdullah.aldamak@ryerson.ca} ; Adel Hatami-Marbini^c ; ^{adel.hatamimarbini@dmu.ac.uk} ; Saeed Zolfaghari^b ; ^{zolfaghari@ryerson.ca}
• 关键词：Data envelopment analysis ; Optimistic DEA ; Pessimistic DEA ; FDH ; Super-efficiency
• 刊名：Computers & Industrial Engineering
• 出版年：2016
• 出版时间：November 2016
• 年：2016
• 卷：101
• 期：Complete
• 页码：466-478
• 全文大小：648 K
• 卷排序：101

文摘

We develop authentic optimistic and pessimistic DEA models without convexity. The input- and output oriented FDH models are considered. In order to improve the discrimination power, extended super-efficiency FDH models are proposed. We bypass the infeasibility problem in the proposed FDH super models. Numerical results based on a case study from the literature are provided and compared with other models.