A nonmonotone filter method for nonlinear

Chungen Shen Shanghai Finance University Sven Leyffer Argonne National Laboratory Roger Fletcher University of Dundee

TBD mathscidoc:1911.43011

Comput Optim Appl, 52, 583-607, 2012
We propose a new nonmonotone filter method to promote global and fast local convergence for sequential quadratic programming algorithms. Our method uses two filters: a standard, global g-filter for global convergence, and a local nonmonotone l-filter that allows us to establish fast local convergence. We show how to switch between the two filters efficiently, and we prove global and superlinear local convergence. A special feature of the proposed method is that it does not require second-order correction steps. We present preliminary numerical results comparing our implementation with a classical filter SQP method.
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@inproceedings{chungen2012a,
  title={A nonmonotone filter method for nonlinear},
  author={Chungen Shen, Sven Leyffer, and Roger Fletcher},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191125144226443381522},
  booktitle={Comput Optim Appl},
  volume={52},
  pages={583-607},
  year={2012},
}
Chungen Shen, Sven Leyffer, and Roger Fletcher. A nonmonotone filter method for nonlinear. 2012. Vol. 52. In Comput Optim Appl. pp.583-607. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191125144226443381522.
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