PřF:FC200 Numerical optimization

FC200 Numerical optimization

Faculty of Science
Spring 2023

Extent and Intensity

2/0. 2 credit(s). Type of Completion: zk (examination).

Teacher(s)

prof. RNDr. Josef Humlíček, CSc. (lecturer)

Guaranteed by

Course Enrolment Limitations

The course is offered to students of any study field.

Course objectives

The aim is at algorithms and utilisation of numerical optimalisation methods.

Syllabus

Minimization, maximization, optimization in science and technology. Unconditioned minimizing of the square function. The linear model in statistics. Cholesky method. Example - refractive index of quartz. Minimizing functions of one variable. Search in point networks, the golden section. Rosenbock and Brent method. Example - Wigner-Breit distribution position from maximum likelihood. Minimizing functions of more variables. Nelder-Meade method, Powell method. The steepest descent, conjugated gradients, Taylor expansion. Marquardt-Levenberg method. Variable metric. Example - testing the effectiveness with the Rosenbrock function. Linear programming. Simplex method. An example of resources optimizing.

Literature

HUMLÍČEK, Josef. Základní metody numerické matematiky. Vyd. 1. Praha: Státní pedagogické nakladatelství, 1981, 171 s. info
HUMLÍČEK, Josef. Statistické zpracování výsledků měření. 1. vyd. Brno: Rektorát UJEP, 1984, 101 s. info

Language of instruction

Czech

Further Comments

The course is taught once in two years.
The course is taught: every week.