caa a22 4500 465775012 CHVBK 20180323111939.0 cr unu---uuuuu 170327e19901201xx s 000 0 eng 10.1007/BF02055200 doi (NATIONALLICENCE)springer-10.1007/BF02055200 Sachs Ekkehard Fachbereich IV-Mathematik, Universität Trier, Postfach 3825, D-5500, Trier, Germany aut Convergence of algorithms for perturbed optimization problems [Elektronische Daten] [Ekkehard Sachs] Infinite-dimensional optimization problems occur in various applications such as optimal control problems and parameter identification problems. If these problems are solved numerically the methods require a discretization which can be viewed as a perturbation of the data of the optimization problem. In this case the expected convergence behavior of the numerical method used to solve the problem does not only depend on the discretized problem but also on the original one. Algorithms which are analyzed include the gradient projection method, conditional gradient method, Newton's method and quasi-Newton methods for unconstrained and constrained problems with simple constraints. J.C. Baltzer A.G. Scientific Publishing Company, 1990 Annals of Operations Research Baltzer Science Publishers, Baarn/Kluwer Academic Publishers 27/1(1990-12-01), 311-341 0254-5330 27:1<311 1990 27 10479 https://doi.org/10.1007/BF02055200 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF02055200 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Sachs Ekkehard Fachbereich IV-Mathematik, Universität Trier, Postfach 3825, D-5500, Trier, Germany aut NATIONALLICENCE 773 0- Annals of Operations Research Baltzer Science Publishers, Baarn/Kluwer Academic Publishers 27/1(1990-12-01), 311-341 0254-5330 27:1<311 1990 27 10479 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer