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Smoothing Approximation to the Square‐Order Exact Penalty Functions for Constrained Optimization

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  • Shujun Lian
  • Jinli Han

Abstract

A method is proposed to smooth the square‐order exact penalty function for inequality constrained optimization. It is shown that, under some conditions, an approximately optimal solution of the original problem can be obtained by searching an approximately optimal solution of the smoothed penalty problem. An algorithm based on the smoothed penalty functions is given. The algorithm is shown to be convergent under mild conditions. Two numerical examples show that the algorithm seems efficient.

Suggested Citation

  • Shujun Lian & Jinli Han, 2013. "Smoothing Approximation to the Square‐Order Exact Penalty Functions for Constrained Optimization," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnljam:v:2013:y:2013:i:1:n:568316
    DOI: 10.1155/2013/568316
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    References listed on IDEAS

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    1. X. L. Sun & D. Li, 1999. "Value-Estimation Function Method for Constrained Global Optimization," Journal of Optimization Theory and Applications, Springer, vol. 102(2), pages 385-409, August.
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    Cited by:

    1. S. Kabbadj, 2020. "Theoretical Aspect of Diagonal Bregman Proximal Methods," Journal of Applied Mathematics, John Wiley & Sons, vol. 2020(1).

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