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On the performance assessment and comparison of stochastic multiobjective optimizers

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Parallel Problem Solving from Nature — PPSN IV (PPSN 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1141))

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Abstract

This work proposes a quantitative, non-parametric interpretation of statistical performance of stochastic multiobjective optimizers, including, but not limited to, genetic algorithms. It is shown that, according to this interpretation, typical performance can be defined in terms analogous to the notion of median for ordinal data, as can other measures analogous to other quantiles.

Non-parametric statistical test procedures are then shown to be useful in deciding the relative performance of different multiobjective optimizers on a given problem. Illustrative experimental results are provided to support the discussion.

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References

  1. C. M. Fonseca and P. J. Fleming, “An overview of evolutionary algorithms in multiobjective optimization,” Evolutionary Computation, vol. 3, pp. 1–16, Spring 1995.

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  2. W. J. Conover, ed., Practical Nonparametric Statistics. New York: Wiley, 1971.

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  3. C. M. Fonseca, Multiobjective Genetic Algorithms with Application to Control Engineering Problems. PhD thesis, University of Sheffield, 1995.

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  4. C. M. Fonseca and P. J. Fleming, “Multiobjective optimal controller design with genetic algorithms,” in Proc. IEE Control'94 International Conference, vol. 1, (Warwick, U.K.), pp. 745–749, 1994.

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  5. C. M. Fonseca and P. J. Fleming, “Multiobjective genetic algorithms made easy: Selection, sharing and mating restriction,” in First IEE/IEEE International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, (Sheffield, UK), pp. 45–52, The Institution of Electrical Engineers, 1995.

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Authors and Affiliations

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

    Carlos M. Fonseca & Peter J. Fleming

Authors
  1. Carlos M. Fonseca
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  2. Peter J. Fleming
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Editor information

Hans-Michael Voigt Werner Ebeling Ingo Rechenberg Hans-Paul Schwefel

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© 1996 Springer-Verlag Berlin Heidelberg

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Fonseca, C.M., Fleming, P.J. (1996). On the performance assessment and comparison of stochastic multiobjective optimizers. In: Voigt, HM., Ebeling, W., Rechenberg, I., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN IV. PPSN 1996. Lecture Notes in Computer Science, vol 1141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61723-X_1022

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  • DOI: https://doi.org/10.1007/3-540-61723-X_1022

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61723-5

  • Online ISBN: 978-3-540-70668-7

  • eBook Packages: Springer Book Archive

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