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An Novel Artificial Immune Systems Multi-objective Optimization Algorithm for 0/1 Knapsack Problems

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

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Abstract

Based on the concept of Immunodominance and Antibody Clonal Selection Theory, This paper proposes a new artificial immune system algorithm, Immune Dominance Clonal Multiobjective Algorithm (IDCMA), for multiobjective 0/1 knapsack problems. IDCMA divides the individual population into three sub-populations and adopts different evolution and selection strategies at them, but the update of each sub-population is not carried out all alone. The performance comparisons among IDCMA, SPEA, HLGA, NPGA, NSGA and VEGA show that IDCMA clearly outperforms the other five MOEAs in terms of solution quality.

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Author information

Authors and Affiliations

  1. Institute of Intelligent Information Processing, Xidian University, P.O. Box 224, Xi’an, 710071, China

    Wenping Ma, Licheng Jiao & Maoguo Gong

  2. School of Computer Science and Technology, Xidian University, Xi’an, 710071, China

    Fang Liu

Authors
  1. Wenping Ma
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  2. Licheng Jiao
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  3. Maoguo Gong
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  4. Fang Liu
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Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yuping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  6. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security (Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

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© 2005 Springer-Verlag Berlin Heidelberg

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Ma, W., Jiao, L., Gong, M., Liu, F. (2005). An Novel Artificial Immune Systems Multi-objective Optimization Algorithm for 0/1 Knapsack Problems. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_117

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  • DOI: https://doi.org/10.1007/11596448_117

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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