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Persistent URL http://purl.org/net/epubs/work/12295104
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Record Id 12295104
Title A filter SQP method : local convergence and numerical results
Abstract The work by Gould, Loh, and Robinson (A filter method with unified step computation for nonlinear optimization, SIAM J. Optim., 24 (2014), pp. 175-209) established global convergence of a new filter line search method for finding local first-order solutions to nonlinear and nonconvex constrained optimization problems. A key contribution of that work was that the search direction was computed using the same procedure during every iteration from subproblems that were always feasible and computationally tractable. This contrasts previous filter methods that require a separate restoration phase based on subproblems solely designed to reduce infeasibility. In this paper, we present a nonmonotone variant of our previous algorithm that inherits the previously established global convergence property. In addition, we establish local superlinear convergence of the iterates and provide the results of numerical experiments. The numerical tests validate our method and highlight an interesting numerical trade-of between accepting more (on average lower quality) steps versus fewer (on average higher quality) steps.
Organisation STFC , SCI-COMP , SCI-COMP-CM
Funding Information
Related Research Object(s): 23236965
Language English (EN)
Type Details URI(s) Local file(s) Year
Preprint RAL Preprints RAL-P-2014-012, SIAM J Optimiz 2014. RAL-P-2014-012.pdf 2014
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