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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 as NP-complete problem. Also, ATM maintenance is an intensive service for the bank to sustain its competitive advantage and customer's 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 bank's requirements. Therefore, we have proposed a custom-made genetic algorithm to search for the best possible placement of ATMs with the lease cost. Our proposed method finds solutions under 15 minutes on a desktop computer.