اندازه‌های انعطاف‌پذیر در فرایند تولید: رویکرد جدیدی بر مبنای تحلیل پوششی داده‌ها با مرز دوگانه

نوع مقاله: مقاله پژوهشی

نویسندگان

1 استادیار، گروه ریاضی، واحد پارس‌آباد مغان، دانشگاه آزاد اسلامی، پارس‌آباد مغان، ایران.

2 استاد، گروه ریاضی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران.

چکیده

تحلیل پوششی داده‌ها (DEA) رویکردی برای اندازه‌گیری کارایی نسبی واحدهای تصمیم‌گیری (DMUهای) دارای ورودی‌های متعدد و خروجی‌های متعدد با استفاده از برنامه‌ریزی ریاضی است. در مدل‌های متعارف DEA، ورودی یا خروجی بودن یک اندازه‌ عملکردی باید معلوم باشد. با این حال در برخی از موقعیت‌ها، یک انداز‌ه‌ عملکردی می‌تواند برای برخی از DMUها نقش ورودی و برای برخی دیگر نقش خروجی داشته باشد. چنین متغیرهایی را اندازه‌های انعطاف‌پذیر می‌نامند. این مقاله رویکرد جدید «DEA با مرز دوگانه» را برای طبقه‌بندی اندازه‌های انعطاف‌پذیر معرفی می‌کند. در رویکرد پیشنهادی، هر انداز‌ه‌ انعطاف‌پذیر طوری به عنوان ورودی یا خروجی طبقه‌بندی می‌شود که کارایی DMU مورد ارزیابی بیشینه‌سازی شود. از این رو طبقه‌بندی اندازه‌های انعطاف‌پذیر با استفاده از رویکرد DEAی پیشنهادی، ساده و منطقی‌تر است. یک مثال در مؤسسات آموزش عالی انگلستان، کاربرد رویکرد پیشنهادی را نشان می‌دهد.

کلیدواژه‌ها


عنوان مقاله [English]

Flexible Measures in Production Process: A New Approach Based On Double-Frontier DEA

نویسندگان [English]

  • Hossein Azizi 1
  • Alireza Amirteimoori 2
1 Assistant Professor, Department of Applied Mathematics, Parsabad Moghan Branch, Islamic Azad University, Parsabad Moghan, Iran.
2 Professor, Department of Applied Mathematics, Rasht Branch, Islamic Azad University, Rasht, Iran.
چکیده [English]

Data envelopment analysis (DEA) is an approach for measuring the relative efficiency of a set of decision-making units (DMUs) with multiple inputs and multiple outputs using mathematical programming. In conventional DEA models, a performance measure whether as an input or output usually has to be known. However, in some situations, a performance measure can play input role for some DMUs and output role for others. Such variables are called flexible measures. This paper introduces a new “double-frontier DEA” approach for classification of flexible measures. In the proposed approach, each flexible measure is classified as either input or output, so that the efficiency of the DMU under evaluation is maximized. Therefore, classification of flexible measures using the proposed DEA approach is simpler and more logical. An example in UK higher education institution shows applicability of the proposed approach.

کلیدواژه‌ها [English]

  • Data Envelopment Analysis
  • Efficiency
  • flexible measure

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