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International Conference on Evolutionary Programming

EP 1997: Evolutionary Programming VI pp 177–187Cite as

Evolian: Evolutionary optimization based on lagrangian with constraint scaling

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1213))

Abstract

In this paper, an evolutionary optimization method, Evolian, is proposed for the general constrained optimization problem, which incorporates the concept of (1) a multi-phase optimization process and (2) constraint scaling techniques to resolve problem of ill-conditioning. In each phase of Evolian, the typical evolutionary programming (EP) is performed using an augmented Lagrangian objective function with a penalty parameter fixed. If there is no improvement in the best objective function in one phase, another phase of Evolian is performed after scaling the constraints and then updating the Lagrange multipliers and penalty parameter. This procedure is repeated until a satisfactory solution is obtained. Computer simulation results indicate that Evolian gives outperforming or at least reasonable results for multivariable heavily constrained function optimization as compared to other evolutionary computation-based methods.

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References

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Author information

Authors and Affiliations

  1. Dept. of EE, KAIST, 373-1 Kusong-dong, Yusong-gu, 305-701, Taejon, Korea

    Hyun Myung & Jong-Hwan Kim

Authors
  1. Hyun Myung
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  2. Jong-Hwan Kim
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Editor information

Peter J. Angeline Robert G. Reynolds John R. McDonnell Russ Eberhart

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© 1997 Springer-Verlag Berlin Heidelberg

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Myung, H., Kim, JH. (1997). Evolian: Evolutionary optimization based on lagrangian with constraint scaling. In: Angeline, P.J., Reynolds, R.G., McDonnell, J.R., Eberhart, R. (eds) Evolutionary Programming VI. EP 1997. Lecture Notes in Computer Science, vol 1213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0014810

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  • DOI: https://doi.org/10.1007/BFb0014810

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62788-3

  • Online ISBN: 978-3-540-68518-0

  • eBook Packages: Springer Book Archive

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