2024 ASEE Annual Conference & Exposition

Course scheduling is one of the most time-consuming tasks that department chairs have to perform every academic semester. The course scheduling problem includes assigning a faculty member, the course time/day(s), and a classroom for each offered course. Course scheduling is an NP-complete problem that has been extensively studied over the years.
In this work, rather than addressing the course scheduling problem as a whole, we tackle only the faculty assignment side of the problem. This “divide and conquer” approach reduces the task from an NP-complete problem to a problem for which an optimal solution exists. The goal here is to prioritize assigning the best possible faculty member for each course. Once that is accomplished, class times and locations can be later assigned using other tools. Faculty assignment is prioritized because we believe that no factor is nearly as important as having the most suitable professor teach each course. The time of a qualified professor is by far the most valuable academic resource, above the limited time slots and the limited spatial resources available on campus.
Our faculty-assignment optimization tool uses Linear Programming (LP) with the objective function being the maximization of the overlap between the courses to be offered in a semester and the faculty members’ preferences and skills. This maximizes the chances of every faculty member teaching courses they are interested in. A set of constraints is created to ensure the full coverage of all courses/sections to be offered and also to ensure that no faculty member is assigned to teach more than a pre-determined teaching load limit. The tool is embedded in a web-based application and is available for the public to use.
One of the greatest features of the tool is its objectivity. It generates the faculty-course assignments based on the faculty preferences. It does not favor one faculty member over the other. Disgruntled faculty members who are not pleased with the outcome can no longer be upset with the chair of the department. Additionally, the tool also helps identify structural holes in the department’s depth of coverage across topics, prompting strategic staffing discussions and guiding future faculty searches.
The paper explains how to use the tool and includes some scheduling results for the sake of demonstration. The paper also includes a link for interested future users to access the free, web-based version of the tool to find optimized solutions to their scheduling problems.