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New Sequential Quadratically Constrained Quadratic Programming Method of Feasible Directions and Its Convergence Rate.
- Source :
-
Journal of Optimization Theory & Applications . Apr2006, Vol. 129 Issue 1, p109-130. 22p. - Publication Year :
- 2006
-
Abstract
- This paper discusses optimization problems with nonlinear inequality constraints and presents a new sequential quadratically-constrained quadratic programming (NSQCQP) method of feasible directions for solving such problems. At each iteration, the NSQCQP method solves only one subproblem which consists of a convex quadratic objective function, convex quadratic equality constraints, as well as a perturbation variable and yields a feasible direction of descent (improved direction). The following results on the NSQCQP are obtained: the subproblem solved at each iteration is feasible and solvable: the NSQCQP is globally convergent under the Mangasarian-Fromovitz constraint qualification (MFCQ); the improved direction can avoid the Maratos effect without the assumption of strict complementarity; the NSQCQP is superlinearly and quasiquadratically convergent under some weak assumptions without the strict complementarity assumption and the linear independence constraint qualification (LICQ). [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00223239
- Volume :
- 129
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Journal of Optimization Theory & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 23965064
- Full Text :
- https://doi.org/10.1007/s10957-006-9042-7