Reduction of Insolvency Risk and Total Costs in the Banking Sector using Partners Selection Approach with Genetic Algorithm and MLP Neural Network

Articles in Press

Document Type : Original Article

Authors

1 Department of industrial engineering, South Tehran Branch, Islamic Azad university, Tehran, Iran

2 Department of industrial engineering, south Tehran branch, Islamic Azad University, Tehran,Iran

3 Department of Industrial Engineering, South Tehran Branch. Islamic Azad University, Tehran, Iran

4 Department of Industrial Engineering, South-Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract

Prioritizing strategies to enhance performance in both risk management and cost efficiency is crucial for the banking sector's success and economic stability. One approach is to select partners in such a way that the risk of bank insolvency and total costs are reduced, and the capital adequacy of the bank is increased. So, in this paper, we first created a mathematical model to achieve the above goals in the field of banking using the approach of selecting partners. In this model, three objective functions are considered for the optimal selection of partners, two of which aim to minimize risk and cost, and the last objective is to maximize capital adequacy. To solve this multi-objective model, we implemented an integrated intelligent system. A combination of a multi-objective genetic algorithm and a neural network was used in this system. A multilayer perceptron neural network is used to calculate the nondeterministic parameters based on the data from different periods. The proposed method was evaluated using a numerical example in MATLAB software. The obtained results and their comparison with one of the classic algorithms show the superiority and reliability of this intelligent system. Using this system, the optimal partners can be selected to achieve the set goals. The most important factors in the field of risk have been identified. Then, a meta-heuristic multi-objective algorithm (NSGA-II) along with an intelligent neural network system has been used to optimally select partners. According to this intelligent system, a suitable methodology is presented along with the optimization algorithm.

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International Journal of Engineering

Articles in Press, Accepted Manuscript
Available Online from 27 February 2024

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