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Last update: Hladíková Jana (16.01.2018)
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Last update: Hladíková Jana (16.01.2018)
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. |
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Last update: Hladíková Jana (16.01.2018)
R: Kubíček M.: Optimalizace inženýrských procesů. SNTL Praha 1986. ISBN 05-098-86 A: Individually according to the project orientation. |
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Last update: Hladíková Jana (16.01.2018)
http://www.vscht.cz/mat/Ang/indexAng.html |
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Last update: Hladíková Jana (16.01.2018)
Lectures and exercise classes. |
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Last update: Hladíková Jana (16.01.2018)
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. |
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Last update: Borská Lucie RNDr. Ph.D. (13.05.2019)
Students are expected to have either completed the prerequisite courses Mathematics A and Mathematics B or possess the equivalent knowledge prior to enrolling in the course. |
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Last update: Borská Lucie RNDr. Ph.D. (06.05.2019)
No requirements. |
Teaching methods | ||||
Activity | Credits | Hours | ||
Konzultace s vyučujícími | 0.5 | 14 | ||
Účast na přednáškách | 1 | 28 | ||
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 1 | 28 | ||
Příprava na zkoušku a její absolvování | 1.5 | 42 | ||
Účast na seminářích | 1 | 28 | ||
5 / 5 | 140 / 140 |