Abstract
The business of setting up automated teller machines (ATMs) for banks depends on many factors, such as the price of buying or leasing an ATM, cost of deployment, cost of operation, and ATM characteristics to be deployed. ATM deployment is an intensive computational problem since it is analogous to file server placement, which is known to be an NP-complete problem. Also, ATM maintenance is an intensive service for the bank to sustain its competitive advantage and customers' satisfaction. We have formulated the ATM allocation problem as an optimization problem, where the objective function is to minimize deployment and operational costs subject to the customers' satisfaction and the bank's requirements. Therefore, we have proposed a custom-made, genetic algorithm to search for the best possible placement of ATMs with the least cost. Our proposed method is capable of producing solutions in less than 15 minutes on a desktop computer.