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A multiobjective framework for heavily constrained examination timetabling problems

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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.

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  1. School of Computer Science, Cardiff University, CF24 3AA, Cardiff, UK

    Christine L. Mumford

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  1. Christine L. Mumford
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Correspondence to Christine L. Mumford.

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Mumford, C.L. A multiobjective framework for heavily constrained examination timetabling problems. Ann Oper Res 180, 3–31 (2010). https://doi.org/10.1007/s10479-008-0490-3

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  • DOI: https://doi.org/10.1007/s10479-008-0490-3

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