Optimizing ATM cash flow network management

Diao, Yixin; Sarkar, Ronnie; Jan, Ea-Ee

doi:10.1109/noms.2016.7502963

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…Van Anholt et al (2016) solve the inventory routing problems with pickups and deliveries arising in the replenishment of ATMs. Diao et al (2016) propose a cascaded optimization framework which finds the optimal amount to be replenished and the optimal time for the replenishment. The framework is composed of inner loop optimization and outer loop optimization.…”

Section: Literature Review: Motivating Our Approachmentioning

confidence: 99%

Optimal ATM replenishment policies under demand uncertainty

2019

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The use of Automated Teller Machines (ATMs) has become increasingly popular throughout the world due to the widespread adoption of electronic financial transactions and better access to financial services in many countries. As the network of ATMs is becoming denser while the users are accessing them at a greater rate, the current financial institutions are faced with addressing inventory and replenishment optimal policies when managing a large number of ATMs. An excessive ATM replenishment will result in a large holding cost whereas an inadequate cash inventory will increase the frequency of the replenishments and the probability of stockouts along with customer dissatisfaction. To facilitate informed decisions in ATM cash management, in this paper, we introduce an approach for optimal replenishment amounts to minimize the total costs of money holding and customer dissatisfaction by taking the replenishment costs into account including stock-outs. An important aspect of the replenishment strategy is that the future cash demands are not available at the time of planning. To account for uncertainties in unobserved future cash demands, we use prediction intervals instead of point predictions and solve the cash replenishment-planning problem using robust optimization with linear programming. We illustrate the application of the optimal ATM replenishment policy under future demand uncertainties using data consisting of daily cash withdrawals of 98 ATMs of a bank in Istanbul. We find that the optimization approach introduced in this paper results in significant reductions in costs as compared to common practice strategies.

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Section: Literature Review: Motivating Our Approachmentioning

confidence: 99%

Optimal ATM replenishment policies under demand uncertainty

2019

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Data-Driven Cash Replenishment Planning of Recycling ATMs with Out-of-Cash and Full-of-Cash Risks

Zhou

Wang

et al. 2020

International Journal of Information Systems and Supply Chain Management

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When banks replenish the cash held in automated teller machines (ATMs) it is crucial for them to reduce operational costs while maintaining service level. This article studies the replenishment planning for recycling ATMs, which allow cash deposits to be made as well as withdrawals. The problem is formulated as a special (s, S) inventory model with two safety stocks corresponding to out-of-stock and full-of-stock risks, based on which the ATMs to be replenished each day and the replenishment amount are determined. Experiments with real data show that the model can significantly reduce costs and improve the overall service level.

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Optimizing ATM cash flow network management

Cited by 2 publications

References 3 publications

Optimal ATM replenishment policies under demand uncertainty

Optimal ATM replenishment policies under demand uncertainty

Data-Driven Cash Replenishment Planning of Recycling ATMs with Out-of-Cash and Full-of-Cash Risks

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