A graph-based hyper-heuristic for educational timetabling problems

  • Edmund K. Burke
  • , Barry McCollum
  • , Amnon Meisels
  • , Sanja Petrovic
  • , Rong Qu

    Research output: Contribution to journalArticlepeer-review

    426 Scopus citations

    Abstract

    This paper presents an investigation of a simple generic hyper-heuristic approach upon a set of widely used constructive heuristics (graph coloring heuristics) in timetabling. Within the hyper-heuristic framework, a tabu search approach is employed to search for permutations of graph heuristics which are used for constructing timetables in exam and course timetabling problems. This underpins a multi-stage hyper-heuristic where the tabu search employs permutations upon a different number of graph heuristics in two stages. We study this graph-based hyper-heuristic approach within the context of exploring fundamental issues concerning the search space of the hyper-heuristic (the heuristic space) and the solution space. Such issues have not been addressed in other hyper-heuristic research. These approaches are tested on both exam and course benchmark timetabling problems and are compared with the fine-tuned bespoke state-of-the-art approaches. The results are within the range of the best results reported in the literature. The approach described here represents a significantly more generally applicable approach than the current state of the art in the literature. Future work will extend this hyper-heuristic framework by employing methodologies which are applicable on a wider range of timetabling and scheduling problems.

    Original languageEnglish
    Pages (from-to)177-192
    Number of pages16
    JournalEuropean Journal of Operational Research
    Volume176
    Issue number1
    DOIs
    StatePublished - 1 Jan 2007

    Keywords

    • Graph heuristics
    • Heuristics
    • Hyper-heuristics
    • Tabu search
    • Timetabling

    ASJC Scopus subject areas

    • General Computer Science
    • Modeling and Simulation
    • Management Science and Operations Research
    • Information Systems and Management

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