Immune Inspired Somatic Contiguous Hypermutation for Function Optimisation

  • Johnny Kelsey
  • Jon Timmis
Conference paper

DOI: 10.1007/3-540-45105-6_26

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2723)
Cite this paper as:
Kelsey J., Timmis J. (2003) Immune Inspired Somatic Contiguous Hypermutation for Function Optimisation. In: Cantú-Paz E. et al. (eds) Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2723. Springer, Berlin, Heidelberg

Abstract

When considering function optimisation, there is a trade off between quality of solutions and the number of evaluations it takes to find that solution. Hybrid genetic algorithms have been widely used for function optimisation and have been shown to perform extremely well on these tasks. This paper presents a novel algorithm inspired by the mammalian immune system, combined with a unique mutation mechanism. Results are presented for the optimisation of twelve functions, ranging in dimensionality from one to twenty. Results show that the immune inspired algorithm performs significantly fewer evaluations when compared to a hybrid genetic algorithm, whilst not sacrificing quality of the solution obtained.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Johnny Kelsey
    • 1
  • Jon Timmis
    • 1
  1. 1.Computing LaboratoryUniversity of KentCanterbury, KentUK

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