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An active set limited memory BFGS algorithm for large-scale bound constrained optimization

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  • Yunhai Xiao
  • Dong-Hui Li

Abstract

An active set limited memory BFGS algorithm for large-scale bound constrained optimization is proposed. The active sets are estimated by an identification technique. The search direction is determined by a lower dimensional system of linear equations in free subspace. The implementations of the method on CUTE test problems are described, which show the efficiency of the proposed algorithm. Copyright Springer-Verlag 2008

Suggested Citation

  • Yunhai Xiao & Dong-Hui Li, 2008. "An active set limited memory BFGS algorithm for large-scale bound constrained optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 67(3), pages 443-454, June.
    • Handle: RePEc:spr:mathme:v:67:y:2008:i:3:p:443-454
    DOI: 10.1007/s00186-007-0199-0
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    Cited by:

    1. Gonglin Yuan & Zengxin Wei & Zhongxing Wang, 2013. "Gradient trust region algorithm with limited memory BFGS update for nonsmooth convex minimization," Computational Optimization and Applications, Springer, vol. 54(1), pages 45-64, January.

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