A Quadratically Approximate Framework for Constrained Optimization, Global and Local Convergence
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| Titel: | A Quadratically Approximate Framework for Constrained Optimization, Global and Local Convergence |
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| Autoren: | English Series, Jin Bao Jian |
| Weitere Verfasser: | The Pennsylvania State University CiteSeerX Archives |
| Quelle: | http://jians.gxu.edu.cn/manage/UploadFiles/jjb_124.pdf. |
| Bestand: | CiteSeerX |
| Schlagwörter: | quadratic approximation, algorithm framework |
| Beschreibung: | This paper presents a quadratically approximate algorithm framework (QAAF) for solving general constrained optimization problems, which solves, at each iteration, a subproblem with quadratic objective function and quadratic equality together with inequality constraints. The global convergence of the algorithm framework is presented under the Mangasarian–Fromovitz constraint qualification (MFCQ), and the conditions for superlinear and quadratic convergence of the algorithm framework are given under the MFCQ, the constant rank constraint qualification (CRCQ) as well as the strong second-order sufficiency conditions (SSOSC). As an incidental result, the definition of an approximate KKT point is brought forward, and the global convergence of a sequence of approximate KKT points is analysed. |
| Publikationsart: | text |
| Dateibeschreibung: | application/pdf |
| Sprache: | English |
| Relation: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.669.1558; http://jians.gxu.edu.cn/manage/UploadFiles/jjb_124.pdf |
| Verfügbarkeit: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.669.1558 http://jians.gxu.edu.cn/manage/UploadFiles/jjb_124.pdf |
| Rights: | Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
| Dokumentencode: | edsbas.E02F5C6A |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | This paper presents a quadratically approximate algorithm framework (QAAF) for solving general constrained optimization problems, which solves, at each iteration, a subproblem with quadratic objective function and quadratic equality together with inequality constraints. The global convergence of the algorithm framework is presented under the Mangasarian–Fromovitz constraint qualification (MFCQ), and the conditions for superlinear and quadratic convergence of the algorithm framework are given under the MFCQ, the constant rank constraint qualification (CRCQ) as well as the strong second-order sufficiency conditions (SSOSC). As an incidental result, the definition of an approximate KKT point is brought forward, and the global convergence of a sequence of approximate KKT points is analysed. |
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