Newton's Method for a Class of Weakly Singular Optimal Control Problems
Newton's method for optimal control of highly nonlinear partial differential equations is analyzed using a 2-norm technique. We consider the case where neither the linearization of the equality const...
Newton's method for optimal control of highly nonlinear partial differential equations is analyzed using a 2-norm technique. We consider the case where neither the linearization of the equality const...
Erratum: Weak Sharp Solutions of Variational Inequalities
Xuexiang Huang pointed out that the statement on line 5 of page 184 of [P. Marcotte and D. Zhu, SIAM J. Optim., 9 (1999), pp. 179--189] is invalid, and supplied an alternative proof of the inequality...
Xuexiang Huang pointed out that the statement on line 5 of page 184 of [P. Marcotte and D. Zhu, SIAM J. Optim., 9 (1999), pp. 179--189] is invalid, and supplied an alternative proof of the inequality...
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Pattern Search Methods for Linearly Constrained Minimization
SIAM J. Optim. Volume 10, Issue 3, pp. 917-941 (2000)
Issue Date: 2000
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We extend pattern search methods to linearly constrained minimization. We develop a general class of feasible point pattern search algorithms and prove global convergence to a Karush--Kuhn--Tucker point. As in the case of unconstrained minimization, pattern search methods for linearly constrained problems accomplish this without explicit recourse to the gradient or the directional derivative of the objective. Key to the analysis of the algorithms is the way in which the local search patterns conform to the geometry of the boundary of the feasible region.
©2000 Society for Industrial and Applied Mathematics| Permalink: | http://dx.doi.org/10.1137/S1052623497331373 |
KEYWORDS and AMS
49M30, 65K05
PUBLICATION DATA
1052-6234 (print)
1095-7189 (online)
SIAM