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The superlinear convergence analysis of a nonmonotone BFGS algorithm on convex objective functions

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Abstract

We prove the superlinear convergence of a nonmonotone BFGS algorithm on convex objective functions under suitable conditions.

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Authors and Affiliations

  1. School of Science, East China University of Science and Technology, Shanghai, 200237, P. R. China

    Gong Lin Yuan & Zeng Xin Wei

  2. College of Mathematics and Information Science, Guangxi University, Nanning, 530004, P. R. China

    Gong Lin Yuan & Zeng Xin Wei

Authors
  1. Gong Lin Yuan
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  2. Zeng Xin Wei
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Corresponding author

Correspondence to Gong Lin Yuan.

Additional information

This work is supported by Chinese NSF Grants 10161002, Guangxi NSF Grants 0542043, and Guangxi University SF grands X061041

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Yuan, G.L., Wei, Z.X. The superlinear convergence analysis of a nonmonotone BFGS algorithm on convex objective functions. Acta. Math. Sin.-English Ser. 24, 35–42 (2008). https://doi.org/10.1007/s10114-007-1012-y

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  • DOI: https://doi.org/10.1007/s10114-007-1012-y

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