Bank Efficiency Forecasting Model Based on the Modern Banking Indicators Using a Hybrid Approach of Dynamic Stochastic DEA and Meta-Heuristic Algorithms

Document Type : Research Paper


1 Postdoctoral Research Student, Department of Industrial Management, Faculty of Social Sciences, Imam Khomeini International University (IKIU), Qazvin, Iran

2 Associate Professor, Department of Industrial Management, Faculty of Social Sciences, Imam Khomeini International University (IKIU), Qazvin, Iran


Evaluating the efficiency of banks is crucial to orient their future decisions. In this regard, this paper proposes a new model based on dynamic stochastic data envelopment analysis in a fuzzy environment by considering the modern banking indicators to predict the efficiency of banks, which belongs to the category of NP-hard problems. To deal with the uncertainty in efficiency forecasting, the mean chance theory was used to express the constraints of the model and the expected value in its objective function to forecast the expected efficiency of banks. To solve the proposed model, two hybrid algorithms were designed by combining Monte Carlo (MC) simulation technique with Genetic Algorithm (GA) and Imperialist Competitive Algorithm (ICA). In order to improve the performances of MC-GA and MC-ICA parameters, the Response Surface Methodology (RSM) was applied to set their proper values. In addition, a case study in the modern banking industry was presented to evaluate the performance of the proposed model and the effectiveness of the hybrid algorithms. The results showed that the proposed model had high accuracy in predicting efficiency. Finally, to validate the designed hybrid algorithms, their results were compared with each other in terms of accuracy and convergence speed to the solution.


Main Subjects

Article Title [فارسی]

مدل پیش بینی کارایی بانک براساس شاخص های بانکداری نوین با استفاده از رویکرد هیبریدی تحلیل پوششی داده های تصادفی پویا و الگوریتم های فراابتکاری

Authors [فارسی]

  • علی یعقوبی 1
  • صفر فضلی 2
1 دانشجوی پسادکتری، دپارتمان مدریت صنعتی، دانشکده علوم اجتماعی، دانشگاه بین المللی امام خمینی، قزوین، ایران
2 دانشیار دپارتمان مدیریت صنعتی، دانشکده علوم اجتماعی، دانشگاه بین المللی امام خمینی، قزوین، ایران
Abstract [فارسی]

ارزیابی کارایی شعب بانک ها برای جهت گیری تصمیمات آینده آنها بسیار مهم است. در این راستا، این مقاله مدل جدیدی جهت پیش بینی کارایی شعب بانک ها براساس تحلیل پوششی داده های تصادفی پویا در یک محیط فازی با لحاظ شاخص های بانکداری نوین ارائه می نماید که در گروه مسائل NP-hard قرار دارد. به جهت مواجهه با عدم قطعیت در پیش بینی کارایی، از تئوری متوسط شانس برای بیان محدودیت ها و از امیدریاضی در تابع هدف مدل برای پیش بینی کارایی مورد انتظار بانک ها استفاده شده است. برای حل مدل، دو الگوریتم هیبریدی از ترکیب شبیه سازی مونت کارلو (MC) با الگوریتم های ژنتیک (GA) و رقابت استعماری (ICA) طراحی می گردد. بمنظور بهبود عملکرد الگوریتم های هیبریدی ارائه شده، از تکنیک متدولوژی سطح پاسخ (RSM) جهت تعیین مقادیر پارامترهای آنها استفاده شده است. همچنین یک مطالعه موردی در صنعت بانکداری مدرن بمنظور ارزیابی عملکرد مدل ارائه شده و اثربخشی الگوریتم های هیبریدی ارائه می شود. نتایج نشان داد که مدل ارائه شده دقت بالایی در پیش بینی کارایی دارد. نهایتاً بمنظور اعتبارسنجی الگوریتم های هیبریدی طراحی شده، نتایج آن ها از ابعاد دقت و سرعت همگرایی به جواب مقایسه شده اند.

Keywords [فارسی]

  • تحلیل پوششی داده های تصادفی پویا
  • برنامه ریزی فازی
  • الگوریتم فراابتکاری هیبریدی
  • بانکداری مدرن
  • شبیه سازی مونت کارلو
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