A feasible trust-region algorithm for inequality constrained optimization
The paper presents an algorithm for smooth nonlinearly inequality constrained optimization problems, in which a sequence of feasible iterates is generated by a trust-region sequential quadratic programming subproblem at each iteration. Because of retaining feasibility, the objective function can be...
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| Veröffentlicht in: | Applied mathematics and computation Jg. 173; H. 1; S. 513 - 522 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York, NY
Elsevier Inc
01.02.2006
Elsevier |
| Schlagworte: | |
| ISSN: | 0096-3003, 1873-5649 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | The paper presents an algorithm for smooth nonlinearly inequality constrained optimization problems, in which a sequence of feasible iterates is generated by a trust-region sequential quadratic programming subproblem at each iteration. Because of retaining feasibility, the objective function can be used as a merit function and the subproblems are feasible. Under common assumptions, the algorithm is globally convergent. The numerical results show it is promising. |
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| ISSN: | 0096-3003 1873-5649 |
| DOI: | 10.1016/j.amc.2005.04.080 |