Nonlinear programming without a penalty function or a filter
A new method is introduced for solving equality constrained nonlinear optimization problems. This method does not use a penalty function, nor a barrier or a filter, and yet can be proved to be globally convergent to first-order stationary points. It uses different trust-regions to cope with the nonl...
| Päätekijät: | , |
|---|---|
| Aineistotyyppi: | Report |
| Julkaistu: |
Unspecified
2007
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| _version_ | 1826274065910857728 |
|---|---|
| author | Gould, N Toint, P |
| author_facet | Gould, N Toint, P |
| author_sort | Gould, N |
| collection | OXFORD |
| description | A new method is introduced for solving equality constrained nonlinear optimization problems. This method does not use a penalty function, nor a barrier or a filter, and yet can be proved to be globally convergent to first-order stationary points. It uses different trust-regions to cope with the nonlinearities of the objective function and the constraints, and allows inexact SQP steps that do not lie exactly in the nullspace of the local Jacobian. Preliminary numerical experiments on CUTEr problems indicate that the method performs well. |
| first_indexed | 2024-03-06T22:37:47Z |
| format | Report |
| id | oxford-uuid:5a84ebc0-b1aa-44e8-b797-dfdb42a7712f |
| institution | University of Oxford |
| last_indexed | 2024-03-06T22:37:47Z |
| publishDate | 2007 |
| publisher | Unspecified |
| record_format | dspace |
| spelling | oxford-uuid:5a84ebc0-b1aa-44e8-b797-dfdb42a7712f2022-03-26T17:16:13ZNonlinear programming without a penalty function or a filterReporthttp://purl.org/coar/resource_type/c_93fcuuid:5a84ebc0-b1aa-44e8-b797-dfdb42a7712fMathematical Institute - ePrintsUnspecified2007Gould, NToint, PA new method is introduced for solving equality constrained nonlinear optimization problems. This method does not use a penalty function, nor a barrier or a filter, and yet can be proved to be globally convergent to first-order stationary points. It uses different trust-regions to cope with the nonlinearities of the objective function and the constraints, and allows inexact SQP steps that do not lie exactly in the nullspace of the local Jacobian. Preliminary numerical experiments on CUTEr problems indicate that the method performs well. |
| spellingShingle | Gould, N Toint, P Nonlinear programming without a penalty function or a filter |
| title | Nonlinear programming without a penalty function or a filter |
| title_full | Nonlinear programming without a penalty function or a filter |
| title_fullStr | Nonlinear programming without a penalty function or a filter |
| title_full_unstemmed | Nonlinear programming without a penalty function or a filter |
| title_short | Nonlinear programming without a penalty function or a filter |
| title_sort | nonlinear programming without a penalty function or a filter |
| work_keys_str_mv | AT gouldn nonlinearprogrammingwithoutapenaltyfunctionorafilter AT tointp nonlinearprogrammingwithoutapenaltyfunctionorafilter |