A nonmonotone filter method for nonlinear optimization

Chungen Shen (), Sven Leyffer () and Roger Fletcher ()

Computational Optimization and Applications, 2012, vol. 52, issue 3, 583-607

Abstract: 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. Copyright Springer Science+Business Media, LLC 2012

Keywords: Nonlinear optimization; Nonmonotone filter; Global convergence; Local convergence (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s10589-011-9430-2

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