Comparison of Integer Linear Programming and Dynamic Programming Approaches for ATM Cash Replenishment Optimization Problem

Date

2020-07-01

Author

Ozer, Fazilet
Toroslu, İsmail Hakkı
Karagöz, Pınar

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With the automated teller machine (ATM) cash replenishment problem, banks aim to reduce the number of out-of-cash ATMs and duration of out-of-cash status. On the other hand, they want to reduce the cost of cash replenishment, as well. The problem conventionally involves forecasting ATM cash withdrawals, and then cash replenishment optimization based on the forecast. The authors assume that reliable forecasts are already obtained for the amount of cash needed in ATMs. The focus of the article is cash replenishment optimization. After introducing linear programming-based solutions, the authors propose a solution based on dynamic programming. Experiments conducted on real data reveal that the proposed approach can find the optimal solution more efficiently than linear programming.

Subject Keywords

Cash Replenishment problem, Dynamic programming, Efficient solution, Interest Cost, Linear Programming, Loading Cost, Optimization, Replenishment Schedule

URI

https://hdl.handle.net/11511/41666

Journal

INTERNATIONAL JOURNAL OF APPLIED METAHEURISTIC COMPUTING

DOI

https://doi.org/10.4018/ijamc.2020070107

Collections

Department of Computer Engineering, Article

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Citation Formats

F. Ozer, İ. H. Toroslu, and P. Karagöz, “Comparison of Integer Linear Programming and Dynamic Programming Approaches for ATM Cash Replenishment Optimization Problem,” INTERNATIONAL JOURNAL OF APPLIED METAHEURISTIC COMPUTING, pp. 120–132, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/41666.