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Multiobjective Meta Level Optimization of a Load Balancing Evolutionary Algorithm

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Evolutionary Multi-Criterion Optimization (EMO 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2632))

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Abstract

For any optimization algorithm tuning the parameters is necessary for effective and effcient optimization. We use a meta-level evolutionary algorithm for optimizing the effectiveness and effciency of a load-balancing evolutionary algorithm. We show that the generated parameters perform statistically better than a standard set of parameters and analyze the importance of selecting a good region on the Pareto Front for this type of optimization.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, OH, 45433-7765

    David J. Caswell & Gary B. Lamont

Authors
  1. David J. Caswell
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  2. Gary B. Lamont
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Editor information

Editors and Affiliations

  1. Faculty of Sciences and Technology, Centre for Intelligent Systems, University of the Algarve, Campus de Gambelas, 8005-139, Faro, Portugal

    Carlos M. Fonseca

  2. Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK

    Peter J. Fleming

  3. Department of Electrical Engineering, Computer Engineering and Networks Laboratory, Swiss Federal Institute of Technology, Gloriastraße 35, 8092, Zürich, Switzerland

    Eckart Zitzler  & Lothar Thiele  & 

  4. Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory, Indian Institute of Technology, Kanpur, UP, 208 016, India

    Kalyanmoy Deb

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© 2003 Springer-Verlag Berlin Heidelberg

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Caswell, D.J., Lamont, G.B. (2003). Multiobjective Meta Level Optimization of a Load Balancing Evolutionary Algorithm. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Thiele, L., Deb, K. (eds) Evolutionary Multi-Criterion Optimization. EMO 2003. Lecture Notes in Computer Science, vol 2632. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36970-8_13

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  • DOI: https://doi.org/10.1007/3-540-36970-8_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-01869-8

  • Online ISBN: 978-3-540-36970-7

  • eBook Packages: Springer Book Archive

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