A multiobjective framework for heavily constrained examination timetabling problems

Christine Mumford ()

Annals of Operations Research, 2010, vol. 180, issue 1, 3-31

Abstract: University examination timetabling is a challenging set partitioning problem that comes in many variations, and real world applications usually carry multiple constraints and require the simultaneous optimization of several (often conflicting) objectives. This paper presents a multiobjective framework capable of solving heavily constrained timetabling problems. In this prototype study, we focus on the two objectives: minimizing timetable length while simultaneously optimizing the spread of examinations for individual students. Candidate solutions are presented to a multiobjective memetic algorithm as orderings of examinations, and a greedy algorithm is used to construct violation free timetables from permutation sequences of exams. The role of the multiobjective algorithm is to iteratively improve a population of orderings, with respect to the given objectives, using various mutation and reordering heuristics. Copyright Springer Science+Business Media, LLC 2010

Date: 2010
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DOI: 10.1007/s10479-008-0490-3

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