Skip to main content
SpringerLink
Log in

A New Hyperheuristic Algorithm for Cross-Domain Search Problems

  • Conference paper
Learning and Intelligent Optimization (LION 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7219))

Included in the following conference series:

Abstract

This paper describes a new hyperheuristic algorithm that performs well over a variety of different problem classes. A novel method for switching between working on a single solution and a pool of solutions is proposed. This method is combined with an adaptive strategy that guides the selection of the underlying low-level heuristics throughout the search. The algorithm was implemented based on the HyFlex framework and was submitted as a candidate for the Cross-Domain Heuristic Search Challenge 2011.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cowling, P.I., Kendall, G., Soubeiga, E.: A Hyperheuristic Approach to Scheduling a Sales Summit. In: Burke, E., Erben, W. (eds.) PATAT 2000. LNCS, vol. 2079, pp. 176–190. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  2. Burke, E., Hyde, M., Kendall, G., Ochoa, G., Ozcan, E., Qu, R.: A survey of hyper-heuristics. Computer Science Technical Report No. NOTTCS-TR-SUB-0906241418-2747, School of Computer Science and Information Technology, University of Nottingham (2009)

    Google Scholar 

  3. Burke, E., Curtois, T., Hyde, M., Kendall, G., Ochoa, G., Petrovic, S., Antonio, J.: HyFlex: A Flexible Framework for the Design and Analysis of Hyper-heuristics. In: Multidisciplinary International Scheduling Conference (MISTA 2009), Dublin, Ireland, p. 790 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Database and Artificial Intelligence Group, Vienna University of Technology, Austria

    Andreas Lehrbaum & Nysret Musliu

Authors
  1. Andreas Lehrbaum
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nysret Musliu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Microsoft Research Center, CB3 0FB, Cambridge, UK

    Youssef Hamadi

  2. INRIA Saclay, Université Paris Sud, 91405, Orsay Cedex, France

    Marc Schoenauer

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lehrbaum, A., Musliu, N. (2012). A New Hyperheuristic Algorithm for Cross-Domain Search Problems. In: Hamadi, Y., Schoenauer, M. (eds) Learning and Intelligent Optimization. LION 2012. Lecture Notes in Computer Science, vol 7219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34413-8_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34413-8_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34412-1

  • Online ISBN: 978-3-642-34413-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation