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Convergence Time Analysis for the Multi-objective Counting Ones Problem

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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

We propose a multi-objective generalisation for the well known Counting Ones problem, called the Multi-objective Counting Ones (MOCO) function. It is shown that the problem has four qualitative different regions. We have constructed a convergence time model for the Simple Evolutionary Multi-objective Optimiser (SEMO) algorithm. The analysis gives insight in the convergence behaviour in each region of the MOCO problem. The model predicts a ℓ2 ln ℓ running time, which is confirmed by the experimental runs.

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Author information

Authors and Affiliations

  1. Institute of Information and Computing Sciences, Utrecht University, P.O. Box 80.089, 3508, TB Utrecht, The Netherlands

    Dirk Thierens

Authors
  1. Dirk Thierens
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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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Thierens, D. (2003). Convergence Time Analysis for the Multi-objective Counting Ones Problem. 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_25

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  • DOI: https://doi.org/10.1007/3-540-36970-8_25

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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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