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Improving Artificial Immune System Performance: Inductive Bias and Alternative Mutations

  • Conference paper
Artificial Immune Systems (ICARIS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5132))

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Abstract

Research works related to the Artificial Immune System (AIS) and their applications have been extensively reported during the last decade. In this work, we proposed an inductive bias heuristic called neighbourhood improvement within the classical AIS for improving its performance. We also demonstrated alternative mutation mechanisms for cloning the elite antibodies. Computational experiments using the proposed heuristic and mechanisms to find the near optimal solutions of travelling salesman problems were conducted. The results obtained from the modified AIS were compared with those obtained from other metaheuristics. It was found that the performance of the modified AIS adopting the proposed heuristic and mechanisms outperformed the conventional AIS and other metaheuristics.

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Peter J. Bentley Doheon Lee Sungwon Jung

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© 2008 Springer-Verlag Berlin Heidelberg

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Pongcharoen, P., Chainate, W., Pongcharoen, S. (2008). Improving Artificial Immune System Performance: Inductive Bias and Alternative Mutations. In: Bentley, P.J., Lee, D., Jung, S. (eds) Artificial Immune Systems. ICARIS 2008. Lecture Notes in Computer Science, vol 5132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85072-4_20

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  • DOI: https://doi.org/10.1007/978-3-540-85072-4_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85071-7

  • Online ISBN: 978-3-540-85072-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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