Memetic Computing

, 1:205 | Cite as

Evolving timetabling heuristics using a grammar-based genetic programming hyper-heuristic framework

  • Mohamed Bader-El-Den
  • Riccardo Poli
  • Shaheen Fatima
Special Issue - Regular Research Paper


This paper introduces a Grammar-based Genetic Programming Hyper-Heuristic framework (GPHH) for evolving constructive heuristics for timetabling. In this application GP is used as an online learning method which evolves heuristics while solving the problem. In other words, the system keeps on evolving heuristics for a problem instance until a good solution is found. The framework is tested on some of the most widely used benchmarks in the field of exam timetabling and compared with the best state-of-the-art approaches. Results show that the framework is very competitive with other constructive techniques, and did outperform other hyper-heuristic frameworks on many occasions.


Timetabling Genetic programming Hyper-heuristics Heuristics 


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Mohamed Bader-El-Den
    • 1
  • Riccardo Poli
    • 2
  • Shaheen Fatima
    • 1
  1. 1.Department of Computer ScienceLoughborough UniversityLoughboroughUK
  2. 2.School of Computer Science and Electronic EngineeringUniversity of EssexColchesterUK

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