Dynamic Template Scheduling to Address Uncertainty in Complex Scheduling Problems: a Case Study on Chemotherapy Outpatient Scheduling

Many scheduling problems contain uncertainty. In this paper, we address the uncertainty that arises from requests for appointments that arrive in real time. Requests must be assigned an appointment time immediately (i.e. before all requests are known) for service in the future. We propose dynamic template scheduling, a technique that combines proactive and online optimization and we apply it to the chemotherapy outpatient scheduling problem. We create a proactive template of an expected day in the chemotherapy center using a deterministic optimization model and an empirical distribution made from historical appointment data. As requests for appointments arrive, we use the proactive template to schedule them. When a request arrives that does not fit the template, we update the template online using the deterministic optimization model and the expected future appointments. We test the use of dynamic template scheduling against using a proactive template on its own, the optimal offline solution, and the actual performance of the cancer center. We find improvements in makespan of up to twenty percent when using dynamic template scheduling compared to current practice.