Improving Curriculum Timetabling Models Using Clustering
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This work describes how clustering can aid in the modelling of the curriculum timetabling problem. The practical timetabling problem cannot be solved to proven optimality in any reasonable time. A clustering technique is used to construct additional constraints, that reduce the size of the feasible search space, and improves the quality of the time-tables found within a reasonable computational time. The approach is illustrated using on a real world timetabling problem and a state-of-the-art commercial solver.
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