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International Symposium on Neural Networks

ISNN 2009: Advances in Neural Networks – ISNN 2009 pp 88–97Cite as

A Novel Artificial Immune System for Multiobjective Optimization Problems

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5553))

Abstract

This study presents a novel weight-based multiobjective artificial immune system (WBMOAIS) based on opt-aiNET. The proposed algorithm follows the elementary structure of opt-aiNET, but has the following distinct characteristics: At first,a randomly weighted sum of multiple objectives is used as a fitness function; Secondly, the individuals of the population are chosen from the memory, which is a set of elite solutions. Lastly, in addition to the clonal suppression algorithm similar to that used in opt-aiNET, a new truncation algorithm with similar individuals (TASI) is presented in order to eliminate the similar individuals in memory and obtain a well-distributed spread of non-dominated solutions. Simulation results show WBMOAIS outperforms the vector immune algorithm (VIS) and the elitist non-dominated sorting genetic system (NSGA-II).

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Authors and Affiliations

  1. Zhijiang College, Zhejiang University of Technology, Hangzhou, 310024, China

    Jiaquan Gao & Lei Fang

Authors
  1. Jiaquan Gao
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  2. Lei Fang
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, 501 E. St. Joseph Street, SD 57701, Rapid City, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Gao, J., Fang, L. (2009). A Novel Artificial Immune System for Multiobjective Optimization Problems. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_10

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  • DOI: https://doi.org/10.1007/978-3-642-01513-7_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01512-0

  • Online ISBN: 978-3-642-01513-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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