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A dwindling filter line search algorithm for nonlinear equality constrained optimization

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Abstract

This paper proposes a dwindling filter line search algorithm for nonlinear equality constrained optimization. A dwindling filter, which is a modification of the traditional filter, is employed in the algorithm. The envelope of the dwindling filter becomes thinner and thinner as the step size approaches zero. This new algorithm has more flexibility for the acceptance of the trial step and requires less computational costs compared with traditional filter algorithm. The global and local convergence of the proposed algorithm are given under some reasonable conditions. The numerical experiments are reported to show the effectiveness of the dwindling filter algorithm.

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Authors and Affiliations

  1. School of Mathematics and Informatics, Shanghai Lixin University of Commerce, Shanghai, 201620, China

    Chao Gu

  2. Department of Mathematics, Shanghai Normal University, Shanghai, 200234, China

    Detong Zhu

Authors
  1. Chao Gu
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  2. Detong Zhu
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Correspondence to Detong Zhu.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant Nos. 11201304, 11371253, the Innovation Program of Shanghai Municipal Education Commission under Grant No. 12YZ174, and Group of Accounting and Governance Disciplines (10kq03).

This paper was recommended for publication by Editor DAI Yuhong.

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Gu, C., Zhu, D. A dwindling filter line search algorithm for nonlinear equality constrained optimization. J Syst Sci Complex 28, 623–637 (2015). https://doi.org/10.1007/s11424-014-2024-1

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  • DOI: https://doi.org/10.1007/s11424-014-2024-1

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