Optimization of Cash Logistics in A Cash Center
We model the optimization of cash logistic between a cash center of a commercial bank and the Bank of Thailand in Phuket using a mixed integer linear programming (MILP) problem, which is solved via a Microsoft Excel add-in OpenSolver. Conditions on the cash transport decisions are written as MILP constraints. Historical data of cash withdrawals and deposits between cash centers and the Bank of Thailand are input to a forecasting model (the AAA version of the Exponential Smoothing), which allows for seasonality. Our results show that our forecasts have lower MAPE than the forecasts currently used by the cash center. Using a MILP model combined with a new forecasted value, the cost of cash transportation (transportation cost, sorting cost, cost of fund) reduces by 24 Percent decrease in April 2019, and the sorting cost is not over the budget of 100,000 Baht.
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