Negative data in DEA: Recognizing congestion and specifying the least and the most congested decision making units

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• 作者：Mohammad Khoveyni^a ; ^{mohammadkhoveyni@gmail.com} ; ^{m.khoveyni@iausr.ac.ir} ; Robabeh Eslami^b ; ^{sinhx_2002@yahoo.com} ; ^{Roba_eslami@azad.ac.ir} ; Guo-liang Yang^c ; ^{glyang@casipm.ac.cn}
• 关键词：Data envelopment analysis (DEA) ; Strong and weak congestion ; Negative data in DEA ; Slack variables ; Mixed integer programming (MIP) model
• 刊名：Computers & Operations Research
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：79
• 期：Complete
• 页码：39-48
• 全文大小：744 K
• 卷排序：79

文摘

We introduce a DEA model for identifying PConvex−PConvex−efficient DMUs. We recognize strong and weak congestion in the presence of negative data. We present two MIP models for specifying strongly and weakly most congested DMUs. We propose a method to rank the congested DMUs and identify the least congested DMU. Two examples are presented to highlight the application of our proposed approach.