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A continuously differentiable filled function method for global optimization

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Abstract

In this paper, a new filled function method for finding a global minimizer of global optimization is proposed. The proposed filled function is continuously differentiable and only contains one parameter. It has no parameter sensitive terms. As a result, a general classical local optimization method can be used to find a better minimizer of the proposed filled function with easy parameter adjustment. Numerical experiments show that the proposed filled function method is effective.

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Authors and Affiliations

  1. Department of Basic Science, Jinling Institute of Technology, Nanjing, 211169, People’s Republic of China

    Hongwei Lin

  2. Institute of Information and System Science, Beifang University for Nationalities, Yinchuan, 750021, People’s Republic of China

    Yuelin Gao

  3. School of Computer Science and Technology, Xidian University, Xi’an, Shaanxi, 710071, People’s Republic of China

    Yuping Wang

Authors
  1. Hongwei Lin
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  2. Yuelin Gao
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  3. Yuping Wang
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Correspondence to Yuelin Gao.

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Lin, H., Gao, Y. & Wang, Y. A continuously differentiable filled function method for global optimization. Numer Algor 66, 511–523 (2014). https://doi.org/10.1007/s11075-013-9746-3

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  • DOI: https://doi.org/10.1007/s11075-013-9746-3

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