Course unit code:

A500N1_4D

Course unit title:

Numerical Optimisation

Mode of delivery, planned learning activities and teaching methods:

lecture – 2 hours weekly (on-site method)
laboratory practice – 3 hours weekly (on-site method)

Credits allocated:

6

Recommended semester:

Riadenie procesov – (full-time, attendance method), 1. semester

Level of study:

3.

Prerequisites for registration:

none

Assesment methods:

The course is evaluated as follows: 30% work during the semester, 70% written project. Evaluation scale follows the study rules at STU (passed / failed).

Learning outcomes of the course unit:

The student has knowledge of algorithms and the developing of procedures for solving optimization tasks using numerical methods. The student is able to numerically solve linear, quadratic and selected types of nonlinear optimization problems using available software, while he is able to create his own algorithms for solving optimization tasks.

Course contents:

Floating-point arithmetics, linear and quadratic optimization problems, active set method, interior point method, barrier functions for solving constrained optimization problems, nonlinear optimization problems

Recommended or required reading:

Basic:

• BOYD, Stephen; VANDENBERGHE, Lieven. Convex Optimization. Cambridge: Cambridge Press, 2004. 716 p. ISBN 978-0521-83378-3.

Recommended:

• Beck, Amir, Introduction to Nonlinear Optimization, Society for Industrial and Applied Mathematics, 2014.

Language of instruction:

Slovak

Assessed students in total:

17

A 100 %

B 0 %

C 0 %

D 0 %

E 0 %

FX 0 %

Course supervisor:

doc. Ing. Ľuboš Čirka, PhD.

Last modification:

5. 10. 2019

AIS: 2000/2001