Hyperheuristics: A Tool for Rapid Prototyping in Scheduling and Optimisation

  • Peter Cowling
  • Graham Kendall
  • Eric Soubeiga
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2279)


The term hyperheuristic was introduced by the authors as a high-level heuristic that adaptively controls several low-level knowledgepoor heuristics so that while using only cheap, easy-to-implement low-level heuristics, we may achieve solution quality approaching that of an expensive knowledge-rich approach. For certain classes of problems, this allows us to rapidly produce effective solutions, in a fraction of the time needed for other approaches, and using a level of expertise common among non-academic IT professionals. Hyperheuristics have been successfully applied by the authors to a real-world problem of personnel scheduling. In this paper, the authors report another successful application of hyperheuristics to a rather different real-world problem of personnel scheduling occuring at a UK academic institution. Not only did the hyperheuristics produce results of a quality much superior to that of a manual solution but also these results were produced within a period of only three weeks due to the savings resulting from using the existing hyperheuristic software framework.

Key words

Hyperheuristic Heuristic Rapid prototyping Personnel Scheduling 


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  1. 1.
    K. Baker. Workforce allocation in cyclical scheduling problems: A survey. Operational Research Quarterly, 27(1):155–167, 1976.CrossRefGoogle Scholar
  2. 2.
    J. M. Tien and A. Kamiyama. On manpower scheduling algorithms. SIAM Review, 24(3):275–287, July 1982.zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    D. J. Bradley and J. B. Martin. Continuous personnel scheduling algorithms: a literature review. Journal Of The Society For Health Systems, 2(2):8–23, 1990.Google Scholar
  4. 4.
    G. M. Thompson. A simulated-annealing heuristic for shift scheduling using noncontinuously available employees. Computers and Operations Research, 23(3):275–288, 1996.zbMATHCrossRefGoogle Scholar
  5. 5.
    U. Aickelin and K. A. Dowsland. Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem. Journal of Scheduling, 3:139–153, 2000.zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    K. A. Dowsland. Nurse scheduling with tabu search and strategic oscillation. European Journal of Operational Research, 106:393–407, 1998.zbMATHCrossRefGoogle Scholar
  7. 7.
    B. Dodin, A. A. Elimam, and E. Rolland. Tabu search in audit scheduling. European Journal of Operational Research, 106:373–392, 1998.zbMATHCrossRefGoogle Scholar
  8. 8.
    J. E. Beasley and B. Cao. A tree search algorithm for the crew scheduling problem. European Journal of Operational Research, 94:517–526, 1996.zbMATHCrossRefGoogle Scholar
  9. 9.
    D. Levine. Application of a hybrid genetic algorithm to airline crew scheduling. Computers and operations research, 23(6):547–558, 1996.zbMATHCrossRefGoogle Scholar
  10. 10.
    P. Cowling, G. Kendall, and E. Soubeiga. A hyperheuristic approach to scheduling a sales summit. In E. Burke and W. Erben, editors, Selected Papers of the Third International Conference on the Practice And Theory of Automated Timetabling PATAT’2000, Springer Lecture Notes in Computer Science, 176–190, 2001.Google Scholar
  11. 11.
    P. Cowling, G. Kendall, and E. Soubeiga. A parameter-free hyperheuristic for scheduling a sales summit. Proceedings of the 4th Metaheuristic International Conference, MIC 2001, 127–131.Google Scholar
  12. 12.
    S. C. Wheelwright and S. Makridakis. Forecasting methods for management. John Wiley & Sons Inc, 1973.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Peter Cowling
    • 1
  • Graham Kendall
    • 1
  • Eric Soubeiga
    • 1
  1. 1.Automated Scheduling, optimisAtion and Planning (ASAP) Research Group School of Computer Science and Information Technology (CSIT)The University of NottinghamNottinghamUK

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