Ranking efficient DMUs using the variation coefficient of weights in DEA
محورهای موضوعی : Data Envelopment Analysis
Mojtaba Ziari
1
,
Shokrollah Ziari
2
1 - Member of young researchers and elite club, Firoozkooh branch, Islamic Azad University, Firoozkooh, Iran
2 - Department of Mathematics, Firoozkooh branch, Islamic Azad University, Firoozkooh, Iran
کلید واژه: Data Envelopment Analysis (DEA), Ranking, Extreme efficient, Coefficient of variation,
چکیده مقاله :
One of the difficulties of Data Envelopment Analysis(DEA) is the problem of de_ciency discrimination among efficient Decision Making Units(DMUs) and hence, yielding large number of DMUs as efficient ones. The main purpose of this paper is to overcome this inability. One of the methods for ranking efficient DMUs is minimizing the Coefficient of Variation (CV) for inputs-outputs weights. In this paper, it is introduced a nonlinear model for ranking efficient DMUs based on the minimizing the mean absolute deviation of weights and then we convert the nonlinear model proposed into a linear programming form.
یکی از مشکلات آنالیز پوششی داده ها (DEA) مشکل تبعیض در میان واحدهای تصمیم گیری کارآمد (DMUs) است و بنابراین، منجر به تعداد زیادی DMU به عنوان کار آمد میشود. هدف اصلی این مقاله غلبه بر این ناتوانی است. یکی از روش ها برای رتبه بندیی DMU های کارآمد به حداقل رساندن ضریب تغییرات (CV) برای ورودی-خروجی وزن میباشد. در این مقاله، یک مدا غیر خطی برای رتبه بندی DMU کارآمد مبتنی بر به حداقل رساندن انحراف مطلق میانگین وزن ها معرفی کردیم و سپس ما مدل غیر خطی به یک فرم برنامخ ریزی خطی تبدیل کردیم.
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