Optimal minimal-perturbation university timetabling with faculty preferences
This addresses scheduling inefficiencies for university administrators and faculty, but it is incremental as it applies existing optimization methods to a specific scenario.
The paper tackles the university timetabling problem by minimizing course swaps and maximizing faculty preferences when last-minute changes occur, using an integer linear program (ILP) and demonstrating results through numerical simulations for a hypothetical department.
In the university timetabling problem, sometimes additions or cancellations of course sections occur shortly before the beginning of the academic term, necessitating last-minute teaching staffing changes. We present a decision-making framework that both minimizes the number of course swaps, which are inconvenient to faculty members, and maximizes faculty members' preferences for times they wish to teach. The model is formulated as an integer linear program (ILP). Numerical simulations for a hypothetical mid-sized academic department are presented.