Faculdade de Ciências e Tecnologia

Non Linear Optimization

Code

10808

Academic unit

Faculdade de Ciências e Tecnologia

Department

Departamento de Matemática

Credits

6.0

Teacher in charge

Paula Alexandra da Costa Amaral

Weekly hours

3

Teaching language

Português

Objectives

The goals are:

1- To distinguish the problems by degree of difficulty.

2 - To know optimality conditions and methods for local optima.

3- To understand how the methods "work" for problems with and without constraints, and to be able to compare their merits and weaknesses and convergence rate.

4- To understand the application of some methods for special problems like least squares.

5- To be have an overview of global optimization methods.

Prerequisites

Linear Optimization and Calculus.

Subject matter

1- Unconstrained Problems

1.1 Basics.Newton method for local optima.

1.2. Line search methods.

1.3. Trust region methods.

1.4. Quasi-Newton methods.

 

2- Constrained optimisation

2.1. Basics

2.2. Quadratic Programming.

2.3. Penalities, Barrier and augmented Lagrangian methods.

 

3- Least Squares Problems

4- Brief introduction to global optimization.

Bibliography

Bertsekas, Dimitri P. (1995) -  “Nonlinear Programming”,Athena Scientific;

 

Nash, Stephen G.; Sofer, Ariela, (1996) – “Linear and Nonlinear Programming”, McGraw-Hill;

 

Nocedal, Jorge; Wright, Stephen J., (1999) – “Numerical Optimization”, Springer-Verlag.

Courses