Owing to treatment complexity in chemotherapy administration, nurses are usually required at the beginning, end, and at certain times during treatment to ensure high-quality infusion. It is, thus, critical for an outpatient chemotherapy unit to design a scheduling template that can effectively match nursing resources with treatment requirements. The template contains appointment slots of different lengths and thus allows schedulers to place patients into these appointment slots according to the provider’s order. As the template is often used over a period of several months, there usually exists a mismatch between the daily patient mix and the fixed structure of the given template. Hence, override policies must be employed to adjust to demand. However, these policies are often manually performed by schedulers. A Mixed-Integer Linear Programming (MILP) model has thus been proposed in this thesis to systematically develop optimal override policies in place of the manual process to improve template utilization while maintaining template stability. Numerical experiments based on real-life data from a chemotherapy unit are conducted to demonstrate the effectiveness of the proposed approach.