کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
475282 | 699275 | 2010 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Improving the discrimination power and weights dispersion in the data envelopment analysis
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
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چکیده انگلیسی
Data envelopment analysis (DEA) has been a very popular method for measuring and benchmarking relative efficiency of peer decision making units (DMUs) with multiple input and outputs. Beside of its popularity, DEA has some drawbacks such as unrealistic input–output weights and lack of discrimination among efficient DMUs. In this study, two new models based on a multi-criteria data envelopment analysis (MCDEA) are developed to moderate the homogeneity of weights distribution by using goal programming (GP). These goal programming data envelopment analysis models, GPDEA-CCR and GPDEA-BCC, also improve the discrimination power of DEA.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Operations Research - Volume 37, Issue 1, January 2010, Pages 99–107
Journal: Computers & Operations Research - Volume 37, Issue 1, January 2010, Pages 99–107
نویسندگان
Hasan Bal, H. Hasan Örkcü, Salih Çelebioğlu,