Analysis of Inexact Trust-Region SQP Algorithms

dc.contributor.authorHeinkenschloss, Matthiasen_US
dc.contributor.authorVicente, Luis N.en_US
dc.date.accessioned2018-06-18T17:47:33Zen_US
dc.date.available2018-06-18T17:47:33Zen_US
dc.date.issued1999-09en_US
dc.date.noteSeptember 1999en_US
dc.description.abstractIn this paper we study the global convergence behavior of a class of composite-step trust-region SQP methods that allow inexact problem information. The inexact problem information can result from iterative linear systems solves within the trust-region SQP method or from approximations of first-order derivatives. Accuracy requirements in our trust-region SQP methods are adjusted based on feasibility and optimality of the iterates. In the absence of inexactness our global convergence theory is equal to that of Dennis, El-Alem, Maciel (SIAM J. Optim. 7 (1997), 177-207). If all iterates are feasible, i.e., if all iterates satisfy the equality constraints, then our results are related to the known convergence analyses for trust-region methods with inexact gradient information for unconstrained optimization.en_US
dc.format.extent17 ppen_US
dc.identifier.citationHeinkenschloss, Matthias and Vicente, Luis N.. "Analysis of Inexact Trust-Region SQP Algorithms." (1999) <a href="https://hdl.handle.net/1911/101923">https://hdl.handle.net/1911/101923</a>.en_US
dc.identifier.digitalTR99-18en_US
dc.identifier.urihttps://hdl.handle.net/1911/101923en_US
dc.language.isoengen_US
dc.relation.HasVersionSIAM J. Optim. 12 (2001), no. 2, 283-302en_US
dc.titleAnalysis of Inexact Trust-Region SQP Algorithmsen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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