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Strukturbaum
Die Veranstaltung wurde 1 mal im Vorlesungsverzeichnis SoSe 2023 gefunden:
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Numerical Optimization
Sprache: englisch
Belegpflicht
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Nr.:
102409
Vorlesung
SoSe 2023
4 SWS
jedes 2. Semester
https://www.uni-muenster.de/LearnWeb/learnweb2/course/view.php?id=68054
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Fachbereich:
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Fachbereich 10 Mathematik und Informatik
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Studiengang
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Master/Mathematics, PO 20 (88F23)
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Zugeordnete Lehrperson:
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Wübbeling
verantwort
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Termin:
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Montag
16:00
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18:00
woch
Beginn : 03.04.2023
Ende : 03.07.2023
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Raum :
SRZ 203
Orléans-Ring 12
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Donnerstag
16:00
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18:00
woch
Beginn : 06.04.2023
Ende : 06.07.2023
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Raum :
SRZ 203
Orléans-Ring 12
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| Kommentar: |
In this lecture we will study basic methods and numerical schemes for the solution of optimization problems. Topics include linear optimization, convex optimization, non-convex optimzation as well as PDE-constrained optimzation and - depending on interest - non-smooth optimzation and optimal control. We will discuss optimality conditions and analyse numerical schemes, e.g. with respect to convergence. To participate, please enroll in the Learnweb course available under https://xsso.uni-muenster.de/LearnWeb/learnweb2/course/view.php?id=68054. Use the key Simplex2023. |
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| Literatur: |
- S. Boyd, L. Vandenberghe: Convex Optimization. CUP, 2004
- J. Nocedal, S. Wright: Numerical Optimization. Springer, 2006
- M. Hinze, R. Pinnau, M. Ulbrich, S. Ulbrich: Optimization wich PDE Constraints. Springer, 2008
- W. Alt: Nichtlineare Optimierung. Vieweg, 2003
- D. Luenberger: Introduction to Linear and Nonlinear Programming. Wesley 1972, 1989
- A. Conn, N. Gould, P. Toint: Trust-region methods. SIAM, 2000
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| Voraussetzungen: |
Good knowledge in analysis and numerical methods (for ODEs or PDEs) as well as programming in python. |
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| Leistungsnachweis: |
Successful exercises and exam. |
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| Zielgruppe: |
This lecture is targeted at MSc Mathematik (PO 13 und PO 20) as part I or part II in the specialization scientific computing. |
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eG