Optimal minimal-perturbation university timetabling with faculty preferences
Artificial Intelligence
2020-08-31 v1 Optimization and Control
Abstract
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.
Keywords
Cite
@article{arxiv.2008.12342,
title = {Optimal minimal-perturbation university timetabling with faculty preferences},
author = {Jakob Kotas and Peter Pham and Sam Koellmann},
journal= {arXiv preprint arXiv:2008.12342},
year = {2020}
}