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A New Data Envelopment Analysis (DEA) Model to Determine the Most Efficient Decision Making Unit (DMU) with Imprecise Data | ||
| Advances in Industrial Engineering | ||
| مقاله 1، دوره 49، شماره 2، دی 2015، صفحه 139-148 اصل مقاله (1.1 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jieng.2015.57053 | ||
| نویسندگان | ||
| Bohlool Ebrahimi؛ Morteza Rahmani* ؛ Morteza Khakzar Bafruee | ||
| Technology Development Institute (ACECR), Sharif Branch, Tehran, Iran | ||
| چکیده | ||
| Sohrabi and Nalchigar (2010) proposed a new data envelopment analysis (DEA) model to identify the most efficient decision-making unit (DMU) in presence of imprecise data. In this paper, it is shown that the proposed model is not able to determine the most efficient DMU and is randomly introduced an efficient DMU. In addition, it is shown that this model determines the most efficient DMU in the case of variable return to scale having the same drawback and may be infeasible in some cases. To overcome the drawbacks, some new integrated DEA models are developed. In addition, to find and rank the other most efficient DMUs, an algorithm is proposed. By using the model developed in this paper, the decision maker can find the most efficient DMU by solving only one linear integer programming. The applicability of the proposed model is indicated using imprecise data for 18 suppliers. | ||
| کلیدواژه‌ها | ||
| Data Envelopment Analysis؛ Decision-making unit؛ imprecise data؛ Linear integer programming؛ Supplier Selection | ||
| عنوان مقاله [English] | ||
| مدل جدید تحلیل پوششی داده‌ها برای تعیین کاراترین واحد تصمیم‌گیری با درنظرگرفتن داده‌های غیردقیق | ||
| نویسندگان [English] | ||
| بهلول ابراهیمی؛ مرتضی رحمانی؛ مرتضی خاکزار بفرویی | ||
| دانشجوی دکتری مهندسی صنایع پژوهشکدة توسعة تکنولوژی جهاد دانشگاهی شریف | ||
| چکیده [English] | ||
| سهرابی و نالچیگر (1389)، مدل نوین تحلیل پوششی داده‌ها را برای شناسایی کاراترین واحد تصمیم‌گیری (DMU) با داده‌های غیردقیق ارائه کردند. در این مقاله نشان داده میشود مدل ارائه‌شده لزوماً قادر به تعیین کاراترین DMU نیست و این مدل به‌طورتصادفی یکی از DMUهای کارا را، کاراترین معرفی میکند. همچنین ممکن است مدل ارائه‌شده برای تعیین کاراترین DMU در حالت بازده به مقیاس متغیر غیرممکن باشد. برای غلبه بر این مشکلات، مدل‌های ترکیبی جدیدی ارائه میشود. علاوه‌براین، برای تعیین و رتبه‌بندی سایر DMU های کارا، الگوریتمی پیشنهاد میشود. با به‌کارگیری مدل ارائه‌شده در این پژوهش، فرد تصمیم‌گیرنده می‌تواند کاراترین DMU را فقط با حل یک مدل برنامه‌ریزی خطی عدد صحیح پیدا کند. کاربرد مدل پیشنهادی با درنظرگرفتن داده‌های غیردقیق هجده تأمین‌کننده نشان داده میشود. | ||
| کلیدواژه‌ها [English] | ||
| انتخاب تأمین‌کننده, برنامه‌ریزی خطی عدد صحیح, تحلیل پوششی داده‌ها (DEA), داده‌های غیردقیق, کاراترین DMU | ||
| مراجع | ||
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