Dynamic Optimization Addressing Chemotherapy Outpatient Scheduling

Chemotherapy outpatient scheduling is a complex problem containing uncertainty. Chemotherapy centres are facing increasing demands and they need to increase their efficiency. However, there are very few studies looking at using optimization methods on the chemotherapy scheduling problem.In this dissertation, the chemotherapy outpatient scheduling problem is defined within the scheduling literature. Next, we propose a methodology for choosing what information to include from the problem domain when creating a mathematical model of a real world problem. Several constraint programming models, representing different problem definitions of the deterministic chemotherapy scheduling problem, are created and evaluated for their solvability and the quality of their solutions. The chosen optimization model was tested within a dynamic framework in order to accommodate the dynamism and uncertainty inherent in chemotherapy outpatient scheduling. Termed dynamic template scheduling, this novel algorithm uses the chemotherapy centre's past records and the chosen model to create a template of open slots. 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. To accommodate last minute additions and cancellations to the schedule, we test a shifting algorithm that moves patient start times within a predefined time limit. We demonstrate that chemotherapy centres can use records of past appointments to inform future schedules and that integrating optimization methods into the scheduling procedures can improve efficiency and increase throughput. This research makes a contribution to scheduling research by developing a novel technique that combines proactive and reactive scheduling to address dynamic problems with real-time uncertainty. This research also makes a contribution to health care scheduling applications by solving a case of chemotherapy outpatient scheduling, a practically important problem that has had very little treatment in the literature.Ph.D