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Robustness Approaches for the Examination Timetabling Problem under Data Uncertainty

In the literature the examination timetabling problem (ETTP) is often considered a post-enrollment problem (PE-ETTP). In the real world, universities often schedule their exams before students register using information from previous terms. A direct consequence of this approach is the uncertainty present in the resulting models. In this work we discuss several approaches available in the robust optimization literature. We consider the implications of each approach in respect to the examination timetabling problem and present how the most favorable approaches can be applied to the ETTP. Afterwards we analyze the impact of some possible implementations of the given robustness approaches on two real world instances and several random instances generated by our instance generation framework which we introduce in this work.

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