OPTIMAL ALLOCATION OF CENTRAL BANK ASSETS : A LINEAR PROGRAMMING MODEL

Abstract

This study presents a linear programming model to optimize the virtual alloca tion of funds by the central bank of a country to various banks and allied sectors, with the objective of maximizing interest revenue while minimizing bad debt. The model assumes a total asset of Rs. 5 trillion, which are allocated to affiliated and registered banks, namely XYZ, ABC, NABARD, BNP, and IBS. These banks further invest the allocated funds in at least five sectors, namely agriculture, power plants, medical research, manufacturing industry, and education. Here, the objective func tion combines interest revenue and bad debt, with the goal of maximizing interest revenue while keeping bad debt at zero. The model includes eight constraints, such as total allocation limits for each bank, overall bad debt ratio, and sector-specific requirements. The problem is solved using computer software and the optimal allo cation of funds is determined. Although the model is hypothetical, it demonstrates the potential of linear programming in optimizing resource allocation in the banking sector. The study highlights the importance of considering multiple factors, such as interest rates and bad debt ratios, in making investment decisions. The findings can improve policy decisions and help banks optimize their investment strategies to maximize returns while minimizing risks. Further research can focus on incorporat ing real-world data and additional constraints to enhance the model’s applicability and effectiveness in the banking industry.