A two-phase multiple objective approach to university timetabling utilising optimisation and evolutionary solution methodologies

A two-phase multiple objective approach to university timetabling utilising optimisation and evolutionary solution methodologies

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Article ID: iaor20042637
Country: United Kingdom
Volume: 54
Issue: 11
Start Page Number: 1155
End Page Number: 1166
Publication Date: Nov 2003
Journal: Journal of the Operational Research Society
Authors: , ,
Keywords: education, programming: multiple criteria
Abstract:

The timetabling problem is generally large, highly constrained and discrete in nature. This makes solution by exact optimisation methods difficult. Therefore, often a heuristic search is deemed acceptable providing a simple (non-optimal) solution. This paper discusses the timetabling problem for a university department, where a large-scale integer goal programming (IGP) formulation is implemented for its efficient optimal solution in two phases. The first phase allocates lectures to rooms and the second allocates start-times to lectures. Owing to the size and complicated nature of the model, an initial analysis procedure is employed to manipulate the data to produce a more manageable model, resulting in considerable reductions in problem size and increase of performance. Both phases are modelled as IGPs. Phase 1 is solved using a state-of-the-art IGP optimization package. However, due to the scale of the model, phase 2 is solved to optimality using a genetic algorithm approach.

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