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A dwindling filter algorithm with a modified subproblem for nonlinear inequality constrained optimization

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Abstract

The authors propose a dwindling filter algorithm with Zhou’s modified subproblem for nonlinear inequality constrained optimization. The feasibility restoration phase, which is always used in the traditional filter method, is not needed. Under mild conditions, global convergence and local superlinear convergence rates are obtained. Numerical results demonstrate that the new algorithm is effective.

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Authors and Affiliations

  1. School of Mathematics and Information, 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 Chao Gu.

Additional information

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

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Gu, C., Zhu, D. A dwindling filter algorithm with a modified subproblem for nonlinear inequality constrained optimization. Chin. Ann. Math. Ser. B 35, 209–224 (2014). https://doi.org/10.1007/s11401-014-0826-z

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  • DOI: https://doi.org/10.1007/s11401-014-0826-z

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