Resilient Course and Instructor Scheduling in the Mathematics Department at the United States Naval Academy

摘要

In this work, we study the problem of scheduling courses and instructors in the Mathematics Department at the United States Naval Academy (USNA) in a resilient manner. Every semester, the department needs to schedule around 70 instructors and 150-180 course sections into 30 class periods and 30 rooms. We formulate a stochastic integer linear program that schedules these courses, instructors, and rooms. In addition to maximizing instructor preferences and minimizing the number of rooms assigned to instructors, this stochastic integer linear program minimizes the expected number of changes required in the schedule if a disruption were to occur, given a subjective probability distribution over a finite set of possible disruption scenarios. We run our model on a number of instances derived from actual data from the past three years, and investigate the effect of emphasizing different parts of the objective function on the running time and resulting schedules.