Advertisement

Extremal Optimisation and Bin Packing

  • Tim Hendtlass
  • Marcus Randall
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5361)

Abstract

Extremal Optimisation (EO) is a fairly new entrant into the realms of stochastic based optimisation techniques. Its behaviour differs from other more common algorithms as it alters a poorly performing part of the one solution used without regard to the effect this will have on the quality of the solution. While this means that its performance on assignment problems may be poor if used on its own, this same ‘failing’ makes it a very suitable base for a meta-heuristic. An analysis of the performance of naive EO on the classic bin packing problem is performed in this paper. Results are also presented that show that the same naive EO can be used in a meta-heuristic that performs very well.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Alvim, A., Aloise, D., Glover, F., Ribeiro, C.: Local search for the bin packing problem. In: Extended Abstracts of the Third Metaheuristics International Conference, pp. 7–12 (1999)Google Scholar
  2. 2.
    Bak, P.: How Nature Works. Springer, Heidelberg (1996)CrossRefzbMATHGoogle Scholar
  3. 3.
    Bak, P., Sneppen, K.: Punctuated equilibrium and criticality in a simple model of evolution. Physical Review Letters 71, 4083–4086 (1993)CrossRefGoogle Scholar
  4. 4.
    Bak, P., Tang, C., Wiesenfeld, K.: Self-organized criticality: an explanation of 1/f noise. Physical Review Letters 59, 381–384 (1987)CrossRefGoogle Scholar
  5. 5.
    Beasley, J.: OR-Library: Distributing test problems by electronic mail. Journal of the Operational Research Society 41, 1069–1072 (1990)CrossRefGoogle Scholar
  6. 6.
    Boettcher, S.: Extremal optimization of graph partitioning at the percolation threshold. Journal of Physics A: Mathematical and General 86, 5201–5211 (1999)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Boettcher, S., Percus, A.G.: Extremal optimization for graph partitioning. Physical Review E 64, 26–114 (2001)CrossRefGoogle Scholar
  8. 8.
    Boettcher, S., Percus, A.G.: Optimization with extremal dynamics. Physical Review Letters 86, 5211–5214 (2001)CrossRefzbMATHGoogle Scholar
  9. 9.
    Levine, J., Ducatelle, F.: Ant colony optimisation and local search for bin packing and cutting stock problems. Journal of the Operational Research Society 55, 705–716 (2004)CrossRefzbMATHGoogle Scholar
  10. 10.
    Randall, M.: Enhancements to extremal optimisation for generalised assignment. In: Randall, M., Abbass, H., Wiles, J. (eds.) ACAL 2007. LNCS, vol. 4828, pp. 369–380. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Tim Hendtlass
    • 1
  • Marcus Randall
    • 2
  1. 1.Faculty of Information and Communication TechnologiesSwinburne University of TechnologyVictoriaAustralia
  2. 2.School of Information TechnologyBond UniversityQueenslandAustralia

Personalised recommendations