A multi-stage IP-based heuristic for class timetabling and trainer rostering

We consider an academic timetabling and rostering problem involving periodic retraining of large numbers of employees at an Australian electricity distributor. This problem is different from traditional high-school and university timetabling problems studied in the literature in several aspects. We propose a three-stage heuristic consisting of timetable generation, timetable improvement, and trainer rostering. Large-scale integer linear programming (ILP) models for both the timetabling and the rostering components are proposed, and several unique operational constraints are discussed. We show that this solution approach is more flexible regarding constraints and objectives, and is able to generate solutions of superior quality to the existing software system in use at the organisation.