Article ID: | iaor20164566 |
Volume: | 28 |
Issue: | 4 |
Start Page Number: | 781 |
End Page Number: | 794 |
Publication Date: | Nov 2016 |
Journal: | INFORMS Journal on Computing |
Authors: | Bykov Yuri, Burke Edmund K |
Keywords: | education, combinatorial optimization, heuristics |
This paper presents a new methodology for university exam timetabling problems, which draws upon earlier work on the Great Deluge metaheuristic. The new method introduces a ‘flexible’ acceptance condition. Even a simple variant of this technique (with fixed flexibility) outperforms the original Great Deluge algorithm. Moreover, it enables a run‐time adaptation of an acceptance condition for each particular move. We investigate the adaptive mechanism where the algorithm accepts the movement of exams in a way that is dependent upon the difficulty of assigning that exam. The overall motivation is to encourage the exploration of a wider region of the search space. We present an analysis of the results of our tests of this technique on two international collections of benchmark exam timetabling problems. We show that 9 of 16 solutions in the first collection and 11 of 12 solutions in the second collection produced by our technique have a higher level of quality than previously published methodologies.