Subjects

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Optimization of Engineering Processes - N413011

Title:	Optimalizace inženýrských procesů
Guaranteed by:	Department of Mathematics (413)
Faculty:	Faculty of Chemical Engineering
Actual:	from 2013 to 2019
Semester:	winter
Points:	winter s.:5
E-Credits:	winter s.:5
Examination process:	winter s.:
Hours per week, examination:	winter s.:2/2, C+Ex [HT]
Capacity:	24 / 24 (unknown)
Min. number of students:	unlimited
Language:	Czech
Teaching methods:	full-time
Teaching methods:	full-time
Level:
For type:

Guarantor:	Kubíček Milan prof. RNDr. CSc.
Is interchangeable with:	M413005

Examination dates Schedule

Annotation -

The course is oriented on ability of formulation of optimization problem based on mathematical model of a process. Methods of classical analysis for unconstained and constrained extrema are discussed. Basic methods of linear, nonlinear and dynamic programming are introduced. Vector optimization problems are discussed. Methods are demonstrated on selected engineering problems.

Last update: Kubíček Milan (01.08.2013)

Aim of the course -

Students will be able to understand and formulate optimization problem and to solve it in simple cases, to use suitable software in more complicated cases, to analyze the problem and suggest a solution.

Last update: Kubíček Milan (01.08.2013)

Literature -

R: Kubíček M.: Optimalizace inženýrských procesů. SNTL Praha 1986. ISBN 05-098-86

A: Individually according to the project orientation.

Last update: TAJ413 (28.08.2013)

Learning resources -

http://www.vscht.cz/mat/Ang/indexAng.html

Last update: Kubíček Milan (27.08.2013)

Teaching methods -

Lectures and exercise classes.

Last update: TAJ413 (01.08.2013)

Syllabus -

1. Formulation of optimization problem.

2. Extrema of functions of real variables-methods of classical analysis.

3. Free extremum, extremum with equality constraints.

4. Extremum with inequality constraints.

5. Linear programming.

6. Simplex method.

7. Nonlinear programming.

8. Methods of adaptive search.

9. Gradient methods.

10. Penalty functions.

11. Elements of dynamic programming.

12. Example of sources distribution.

13. Vector optimization.

14. Construction of Pareto compromise set.

Last update: Kubíček Milan (30.07.2013)

Registration requirements -

Mathematics I, Mathematics II.

Last update: Kubíček Milan (01.08.2013)

Teaching methods
	Activity	Credits	Hours
	Konzultace s vyučujícími	0.5	14
	Obhajoba individuálního projektu	0.1	3
	Účast na přednáškách	1	28
	Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi	1	28
	Práce na individuálním projektu	0.5	14
	Příprava na zkoušku a její absolvování	0.9	25
	Účast na seminářích	1	28
		5 / 5	140 / 140

Coursework assessment
Form	Significance
Regular attendance	20
Defense of an individual project	10
Examination test	30
Continuous assessment of study performance and course -credit tests	10
Oral examination	30