Optimizing ATM Cash Replenishment using nonlinear programming

Abstract

The objective of this work is to use a NonLinear programming based optimization model for ATM cash replenishment that: 1. Minimizes the total cost of cash replenishment while ensuring that all ATMs have adequate cash levels. 2. Takes into account factors like ATM usage patterns, cash demand, cash storage capacity, and budget constraints. 3. Can be implemented in real-world ATM networks to reduce operational costs and improve cash management. This study focuses on establishing a conceptual frame work for optimizing the cost of cash replenishment for networks of ATMs and minimizing the cash-dry instances at individual ATM. The objective is to minimize the total cost of logistics, inventory, and improving customer service satisfaction. This approach considers the combination of following techniques: - Time series forecasting accounting for seasonality, trend and local calendar events - Inventory theory – determining frequency and quantity of cash to be replenished for each ATM .