Dynamic optimization of chemotherapy outpatient scheduling with uncertainty

Chemotherapy outpatient scheduling is a complex, dynamic, uncertain problem. Chemotherapy centres are facing increasing demands and they need to increase their efficiency; however there are very few studies looking at using optimization technology on the chemotherapy scheduling problem. We address dynamic uncertainty that arises from requests for appointments that arrive in real time and uncertainty due to last minute scheduling changes. We propose dynamic template scheduling, a novel 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 centre using a deterministic optimization model and a sample of appointments. As requests for appointments arrive, we use the template to schedule them. When a request arrives that does not fit the template, we update the template online using the optimization model and a revised set of appointments. To accommodate last minute additions and cancellations to the schedule, we propose a shuffling algorithm that moves appointment start times within a predefined time limit. We test the use of dynamic template scheduling against the optimal offline solution and the actual performance of the cancer centre. We find improvements in makespan of up to 20 % when using dynamic template scheduling compared to current practice.