Robust automated timetabling. Computer Science PhD

The University of Exeter EPSRC DTP (Engineering and Physical Sciences Research Council Doctoral Training Partnership) is offering up to 4 fully funded doctoral studentships for 2019/20 entry. Students will be given sector-leading training and development with outstanding facilities and resources. Studentships will be awarded to outstanding applicants, the distribution will be overseen by the University’s EPSRC Strategy Group in partnership with the Doctoral College.

Supervisors:
Prof. Jonathan Fieldsend, Department of Computer Science, College of Engineering, Mathematics and Physical Sciences
Prof. Ed Keedwell, Department of Computer Science, College of Engineering, Mathematics and Physical Sciences

Project description:
Timetabling and scheduling problems occur widely in both private and public sectors. (In)effective schedules can have a significant effect on profits and the efficient use of resources along with consumer and employee satisfaction.

Alongside the effectiveness of a given timetable/schedule, the robustness/fragility of a deployed solution when coping with changes in demand/resource availability is often also an important concern.

A prototypical timetabling problem is university course timetabling. With hundreds of rooms, hundreds of modules, hundreds of staff and thousands of students, the search domain is far too vast to be exhaustively enumerated to find an optimal solution satisfying the wide range of constraints needing to be satisfied. Instead, heuristic search algorithms are typically employed by a team of staff to develop the final timetable to be used.

As a university grows in size, and the choice of modules available to a student both within and outside their department expands, so the complexity the timetabling task also increases. Beyond this, developing a timetable which has flexibility to cope with staff illness, and deal with variation in projected enrolments, complicates the task further.

This project will develop and apply timetabling algorithms for the university timetabling domain, using e.g. hyper-heuristics, converting the constraints to be satisfied by a solution as criteria in a many-objective optimisation problem, and developing criteria to effectively assess the robustness of a solution.