# Optimization Methods

UNIVERSITÀ DELLA SVIZZERA ITALIANA
A Mendrisio (Svizzera)

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## Informazioni importanti

 Tipologia Corso Luogo Mendrisio (Svizzera)
• Corso
• Mendrisio (Svizzera)
Descrizione

Descrizione Optimization is of fundamental importance in virtually all branches of science and technology. As a consequence, optimization methods find their applications in numerous fields, starting from, e.g., network flow and ranging over shape optimization in engineering to optimal control problems. This course provides an introduction into the most important methods and techniques in discrete and continuous optimization. We will present, analyze, implement, and test -along selected problems- methods for discrete and continuous optimization. Particular emphasis will be put on the methodology and the underlying mathematical as well as algorithmic structure. Starting from basic methods as the Simplex method, we will consider different central methods in convex as well as non-convex optimization. This will include optimality conditions, the handling of linear and non-linear constraints, and methods such as interior point methods for convex optimization, Newton's method, Trust-Region methods, and optimal control methods.

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Dove e quando

Inizio Luogo
Consultare
Mendrisio
Tessin, Svizzera
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 Inizio Consultare Luogo MendrisioTessin, Svizzera Visualizza mappa

## Programma

Descrizione

Optimization is of fundamental importance in virtually all branches of science and technology. As a consequence, optimization methods find their applications in numerous fields, starting from, e.g., network flow and ranging over shape optimization in engineering to optimal control problems. This course provides an introduction into the most important methods and techniques in discrete and continuous optimization. We will present, analyze, implement, and test -along selected problems- methods for discrete and continuous optimization. Particular emphasis will be put on the methodology and the underlying mathematical as well as algorithmic structure. Starting from basic methods as the Simplex method, we will consider different central methods in convex as well as non-convex optimization. This will include optimality conditions, the handling of linear and non-linear constraints, and methods such as interior point methods for convex optimization, Newton's method, Trust-Region methods, and optimal control methods.

REFERENCES

• Nocedal Wright, Numerical Optimisation;
• Trust-Region Methods; Conn Gould Toint.
• Practical Methods of Optimisation; R. Fletcher.
• Numerical Optimisation, Series: Springer Series in Operations Research and Financial Engineering, Nocedal, Jorge, Wright, Stephen 2nd ed., 2006, XXII, 664 p. 85 illus., www.springer.com/mathematics/book/978-0-387-30303-1