یک روش ترکیببی جدید بر اساس تحلیل پوششی داده ها و شبکه عصبی برای بهینه سازی ارزیابی عملکرد

Subject Areas : International Journal of Industrial Mathematics

علی نمکین ¹ ( گروه مهندسی صنایع، واحد علوم و تحقیقات تهران، دانشگاه آزاد اسلامی، تهران، ایران. )
سید اسماعیل نجفی ² ( گروه مهندسی صنایع، واحد علوم و تحقیقات تهران، دانشگاه آزاد اسلامی، تهران، ایران. )
محمد فلاح ³ ( گروه مهندسی صنایع، واحد علوم و تحقیقات تهران، دانشگاه آزاد اسلامی، تهران، ایران. )
مهرداد جوادی ⁴ ( گروه مهندسی صنایع، واحد علوم و تحقیقات تهران، دانشگاه آزاد اسلامی، تهران، ایران. )

Received: 2020-06-24 Accepted : 2021-04-23 Published : 2021-10-01

Keywords: تحلیل پوششی داده ها – شبکه عصبی مصنوعی, کارایی,

Abstract :

در این مقاله ، یک روش جدید ترکیبی از شبکه های عصبی پرسپترون چند لایه و تحلیل پوششی داده ها ارائه می شود که در آن مقادیر ورودی و خروجی برای تعداد زیادی واحد تصمیم گیرنده به عنوان ورودی های شبکه عصبی تعیین می شود. می توان دید که با بکارگیری شبکه عصبی برای حل مسائل تحلیل پوششی داده ها نیاز به حل مدل مورد نظر برای هر واحد تصمیم گیرنده نیست و لذا الگوریتم ارائه شده زمان پردازش و استفاده از حافظه را نسبت به آنچه مورد نیاز روش متعارف در تحلیل پوششی داده ها است، به مقدار زیادی کاهش می دهد.جهت بررسی دقت شبکه ارائه شده،  چندمطالعه موردی از جمله مجموعه ای از  500شعبه بانک  مورد استفاده قرار می گیرد.نتایج نشان دهنده دقت بالا وزمان محاسباتی کمتر(اعتبارلازم) مدل ترکیبی پیشنهادی است.

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