Hyper-Heuristics: An Emerging Direction in Modern Search Technology

  • Edmund Burke
  • Graham Kendall
  • Jim Newall
  • Emma Hart
  • Peter Ross
  • Sonia Schulenburg
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 57)


This chapter introduces and overviews an emerging methodology in search and optimisation. One of the key aims of these new approaches, which have been termed hyperheuristics, is to raise the level of generality at which optimisation systems can operate. An objective is that hyper-heuristics will lead to more general systems that are able to handle a wide range of problem domains rather than current meta-heuristic technology which tends to be customised to a particular problem or a narrow class of problems. Hyper-heuristics are broadly concerned with intelligently choosing the right heuristic or algorithm in a given situation. Of course, a hyper-heuristic can be (often is) a (meta-)heuristic and it can operate on (meta-)heuristics. In a certain sense, a hyper-heuristic works at a higher level when compared with the typical application of meta-heuristics to optimisation problems, i.e., a hyper-heuristic could be thought of as a (meta)-heuristic which operates on lower level (meta-)heuristics. In this chapter we will introduce the idea and give a brief history of this emerging area. In addition, we will review some of the latest work to be published in the field.


Hyper-heuristic Meta-heuristic Heuristic Optimisation Search 


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Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Edmund Burke
    • 1
  • Graham Kendall
    • 1
  • Jim Newall
    • 1
  • Emma Hart
    • 2
  • Peter Ross
    • 2
  • Sonia Schulenburg
    • 2
  1. 1.The University of NottinghamUK
  2. 2.Napier UniversityUK

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