Choosing weights for a complete ranking of DMUs in DEA and cross-evaluation

محورهای موضوعی : Data Envelopment Analysis

پریچهر زمانی ¹ (استادیار،دانشکده مهندسی، واحد قم،دانشگاه آزاد اسلامی ،قم، ایران)

تاریخ دریافت : 1396/05/31 تاریخ پذیرش : 1396/08/19 تاریخ انتشار : 1397/09/10

کلید واژه: Data envelopment analysis, Ranking, cross-efficiency, Pure profit,

چکیده مقاله :

Conventional data envelopment analysis (DEA) assists decision makers in distinguishing between efficient and inefficient decision making units (DMUs) in a homogeneous group. However, DEA does not provide more information about the efficient DMUs. One of the interesting research subjects is to discriminate between efficient DMUs. The aim of this paper is ranking all efficient (extreme and non-extreme) DMUs based on defining the new index which is obtained from basic definitions of models. The proposed method has been able to remove the existing deficiencies in some ranking methods and therefore makes a new contribution to DEA ranking.

چکیده انگلیسی:

تحلیل پوششی داده های (DEA) مرسوم به تصمیم گیرنده‌ها (DM) کمک می‌کند تا یک گروه همگن از واحدهای تصمیم‌گیرنده‌ی (DMU) کارا و ناکارا را مشخص نمایند. به هرحال، تحلیل پوششی داده‌ها اطلاعات زیادی در مورد واحدهای تصمیم‌گیرنده کارا نمی‌دهد. یکی از موضوعات جالب تحقیق، تفاوت قایل شدن بین واحدهای تصمیم‌گیرنده کارا است. هدف این مقاله رتبه بندی همه‌ی واحدهای تصمیم گیرنده کارا (رأسی و غیر رأسی) مبنی بر تعریف اندیس جدیدی است که از تعاریف اساسی مدل ها بدست آمده است. روش مطرح شده توانایی حذف کاستی های موجود در بعضی از روشهای رتبه بندی را دارد و به همین دلیل سهم جدیدی در مبحث رتبه بندی تحلیل پوششی داده ها را داراست.

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