Efficient surgical scheduling is essential for maximizing patient outcomes and ensuring optimal use of hospital resources. This thesis proposes and evaluates optimization strategies that incorporate Maximum Waiting Times (MWTs) assigned by doctors—reflecting subjective urgency assessments—and medical urgency quantified objectively through Disability-Adjusted Life Years (DALYs), alongside operational constraints inherent in hospital scheduling. Using real-world surgical data from Erasmus MC, the study aims to identify approaches that effectively balance equity and efficiency in patient prioritization.

The scheduling problem is addressed through Integer Linear Programming (ILP). A core optimization model is developed to minimize the total DALY loss resulting from surgical delays while respecting MWTs. Two extensions of this model are introduced: one explicitly incorporating patient waiting time with a penalty on exceeding MWTs, and another designed to minimize the maximum DALY loss across patients to promote fairness. These three distinct models, each representing a different prioritization strategy, are empirically tested and compared. Additionally, a sensitivity analysis is conducted on the parameter gamma, which penalizes excess waiting time beyond the MWT, to assess how varying emphasis on excess waiting time impacts prioritization outcomes and overall scheduling effectiveness.

The results highlight key trade-offs between system-level efficiency and individual patient fairness, offering actionable insights for improving surgical scheduling practices. The findings support the integration of objective health-outcome metrics alongside clinical judgment into operational decision-making, contributing to a more equitable and effective allocation of surgical resources.

Overall, this study contributes to the field of surgical scheduling by incorporating the objective measure of Disability-Adjusted Life Years (DALYs) into prioritization decisions and promoting ethically grounded, outcome-oriented scheduling policies. The development of three distinct optimization models—balancing medical urgency, fairness, operational constraints, and MWTs—scheds light on the complex trade-offs between minimizing total DALY loss, considering waiting times and subjective urgency, and ensuring equitable patient outcomes.