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A Filled Function Method Dominated by Filter for Nonlinearly Global Optimization

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Listed:
  • Wei Wang
  • Xiaoshan Zhang
  • Min Li

Abstract

This work presents a filled function method based on the filter technique for global optimization. Filled function method is one of the effective methods for nonlinear global optimization, since it can effectively find a better minimizer. Filter technique is applied to local optimization methods for its excellent numerical results. In order to optimize the filled function method, the filter method is employed for global optimizations in this method. A new filled function is proposed first, and then the algorithm and its properties are proved. The numerical results are listed at the end.

Suggested Citation

  • Wei Wang & Xiaoshan Zhang & Min Li, 2015. "A Filled Function Method Dominated by Filter for Nonlinearly Global Optimization," Journal of Applied Mathematics, John Wiley & Sons, vol. 2015(1).
    • Handle: RePEc:wly:jnljam:v:2015:y:2015:i:1:n:245427
    DOI: 10.1155/2015/245427
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    References listed on IDEAS

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    1. Wei Wang & Shaoli Hua & Junjie Tang, 2013. "A Generalized Gradient Projection Filter Algorithm for Inequality Constrained Optimization," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    2. Wei Wang & Shaoli Hua & Junjie Tang, 2013. "A Generalized Gradient Projection Filter Algorithm for Inequality Constrained Optimization," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-6, October.
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