Jennie Gallimore (Committee Member), Pratik Parikh (Advisor), Rosalyn Scott (Committee Member)
Master of Science in Engineering (MSEgr)
This research examines a complex surgical case scheduling problem for a publicly-funded hospital in the Midwest United States. Publicly-funded hospitals are typically under tight budget constraints and these hospitals strive to maximize the utilization of their resources such as beds, staff, equipment, operating rooms, etc. These resources are relatively fixed for a publically funded hospital. A manual scheduling approach followed by this hospital does not guarantee optimal solutions and consequently has led to large variation in the utilization of resources. This real-world problem is described in this research as a multi-day, multi-resource, and patient-priority-based surgical case scheduling problem with the objective of maximizing the weighted sum of surgical case priorities. The surgical case scheduling problem herein is conceptualized as an unequal-sized multi-dimensional multi-bin dual bin-packing problem. A mixed integer programming model is proposed to generate implementable schedules. For each surgical case, the solution obtained will provide detail information about the start time and day of the surgery, the operating room to perform the surgery, and the surgeon's name. Resource availability, patient priorities, and surgical time of the surgeons are key features included in the model. However, the combinatorial nature of this problem limited the MIP model to solving only small problem instances. Consequently, an efficient First Fit Decreasing based heuristic is proposed and its performance is benchmarked against the MIP model. The benefit of pooling surgical cases over the commonly used First Come First Serve scheduling policy is also demonstrated. Results quantify the extent to which pooling can increase the number of high priority surgeries performed.
Department or Program
Department of Biomedical, Industrial & Human Factors Engineering
Year Degree Awarded
Copyright 2011, all rights reserved. This open access ETD is published by Wright State University and OhioLINK.