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A Faster Clonal Selection Algorithm for Expensive Optimization Problems

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Artificial Immune Systems (ICARIS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6209))

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Abstract

Artificial Immune Systems (AISs) are computational methods, inspired by the biological immune system, that can be applied to solve optimization problems. In this paper we propose the use of a similarity-based surrogate model in conjunction with a clonal selection algorithm in order to improve its performance when solving optimization problems involving computationally expensive objective functions. Computational experiments to assess the performance of the proposed procedure using 23 test-problems from the literature are presented.

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Author information

Authors and Affiliations

  1. Laboratório Nacional de Computação Científica – LNCC,  

    Heder S. Bernardino & Helio J. C. Barbosa

  2. Universidade Federal do Espírito Santo – CEUNES/UFES,  

    Leonardo G. Fonseca

Authors
  1. Heder S. Bernardino
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  2. Helio J. C. Barbosa
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  3. Leonardo G. Fonseca
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Editor information

Editors and Affiliations

  1. Centre for Emergent Computing, Napier University, 10 Colinton Road, EH10 5DT, Edinburgh, UK

    Emma Hart  & Chris McEwan  & 

  2. Departments of Computer Science and Electronics, University of York, YO10 5DD, Heslington, York, UK

    Jon Timmis

  3. School of Mathematics, Statistics and Actuarial Science, University of Kent, Cornwallis Building, Canterbury, CT2 7NF, Kent, UK

    Andy Hone

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Bernardino, H.S., Barbosa, H.J.C., Fonseca, L.G. (2010). A Faster Clonal Selection Algorithm for Expensive Optimization Problems. In: Hart, E., McEwan, C., Timmis, J., Hone, A. (eds) Artificial Immune Systems. ICARIS 2010. Lecture Notes in Computer Science, vol 6209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14547-6_11

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  • DOI: https://doi.org/10.1007/978-3-642-14547-6_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14546-9

  • Online ISBN: 978-3-642-14547-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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