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Soft Computing and Industry pp 305–318Cite as

Multi-Constrained Nonlinear Optimization by the Differential Evolution Algorithm

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Abstract

In this article an extension for the Differential Evolution algorithm is proposed for handling nonlinear constraint functions. From the user point of view, the proposed method allows solving multi-constrained global optimization problems virtually as easily as unconstrained problems. User is not assumed to provide a feasible solution as a starting point for searching, as required by many other methods. Furthermore, the user is not required to set any penalty parameters, any weights for individual constraints, or any other additional search parameters, as in cases for most penalty function methods. In comparison with the original Differential Evolution algorithm, only the selection operation was modified with a new selection criteria for handling the constraint functions. The proposed method is demonstrated by solving a suite of seven well-known and difficult test problems.

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Author information

Authors and Affiliations

  1. Laboratory of Information Processing, Lappeenranta University of Technology, P.O.Box 20, FIN-53851, Lappeenranta, Finland

    Jouni Lampinen

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  1. Jouni Lampinen
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Editor information

Editors and Affiliations

  1. Enterprise Integration, Cranfield University, Cranfield, Bedford, MK43 0AL, UK

    Rajkumar Roy PhD

  2. Department of Pattern Recognition, Fraunhofer IPK-Berlin, Pascalstrasse 8-9, Berlin, 10587, Germany

    Mario Köppen Diplom-Phys

  3. Institute of Intelligent Electronics, Helsinki University of Technology, Otakaari 5 A, FIN-02150, Espoo, Finland

    Seppo Ovaska PhD

  4. Department of Information Engineering, Mie University, 1515 Kamihama-cho, Tsu, 514-8507, Japan

    Takeshi Furuhashi PhD

  5. Royal Institute of Technology, NADA/CV AP, 10044, Stockholm, Sweden

    Frank Hoffmann

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© 2002 Springer-Verlag London

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Lampinen, J. (2002). Multi-Constrained Nonlinear Optimization by the Differential Evolution Algorithm. In: Roy, R., Köppen, M., Ovaska, S., Furuhashi, T., Hoffmann, F. (eds) Soft Computing and Industry. Springer, London. https://doi.org/10.1007/978-1-4471-0123-9_26

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  • DOI: https://doi.org/10.1007/978-1-4471-0123-9_26

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1101-6

  • Online ISBN: 978-1-4471-0123-9

  • eBook Packages: Springer Book Archive

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