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A Comparison of Clonal Selection Based Algorithms for Non-Stationary Optimisation Tasks

  • Krzysztof Trojanowski
  • Sławomir T. Wierzchoń
Part of the Advances in Soft Computing book series (AINSC, volume 35)

Abstract

Mammalian immune system and especially clonal selection principle, responsible for coping with external intruders, is an inspiration for a set of heuristic optimization algorithms. Below, a few of them are compared on a set of nonstationary optimization benchmarks. One of the algorithms is our proposal, called AIIA (Artificial Immune Iterated Algorithm). We compare two versions of this algorithm with two other well known algorithms. The results show that all the algorithms based on clonal selection principle can be quite efficient tools for nonstationary optimization.

Keywords

Clonal Selection Main Loop Somatic Hypermutation Immune Algorithm Clonal Selection Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2006

Authors and Affiliations

  • Krzysztof Trojanowski
    • 1
  • Sławomir T. Wierzchoń
    • 1
    • 2
  1. 1.Institute of Computer SciencePolish Academy of SciencesWarszawaPoland
  2. 2.Dep. of Computer ScienceBiałystok Technical UniversityBiałystokPoland

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