Hybrid graph heuristics within a hyper-heuristic approach to exam timetabling problems

Edmund Burke, Moshe Dror, Sanja Petrovic, Rong Qu

Research output: Contribution to journalArticlepeer-review

49 Scopus citations


This paper is concerned with the hybridization of two graph coloring heuristics (Saturation Degree and Largest Degree), and their application within a hyper-heuristic for exam timetabling problems. Hyper-heuristics can be seen as algorithms which intelligently select appropriate algorithms/heuristics for solving a problem. We developed a Tabu Search based hyper-heuristic to search for heuristic lists (of graph heuristics) for solving problems and investigated the heuristic lists found by employing knowledge discovery techniques. Two hybrid approaches (involving Saturation Degree and Largest Degree) including one which employs Case Based Reasoning are presented and discussed. Both the Tabu Search based hyper-heuristic and the hybrid approaches are tested on random and real-world exam timetabling problems. Experimental results are comparable with the best state-of-the-art approaches (as measured against established benchmark problems). The results also demonstrate an increased level of generality in our approach.

Original languageEnglish (US)
Pages (from-to)79-91
Number of pages13
JournalOperations Research/ Computer Science Interfaces Series
StatePublished - 2005
Externally publishedYes


  • Case based reasoning
  • Exam timetabling problems
  • Graph heuristics
  • Hyper-heuristics
  • Knowledge discovery
  • Tabu search

ASJC Scopus subject areas

  • Computer Science(all)
  • Management Science and Operations Research


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