|
|
|
||
Last update: Kubíček Milan prof. RNDr. CSc. (02.10.2018)
|
|
||
Last update: Kubíček Milan prof. RNDr. CSc. (02.10.2018)
Students will be able to: Understand and formulate an optimization problems. Solve the problem in simple cases, use the appropriate software in more complex cases. Classify the problem and propose an efficient solution. Solve the given project. |
|
||
Last update: Borská Lucie RNDr. Ph.D. (06.09.2019)
Kubíček M.: Optimalizace inženýrských procesů. SNTL Praha 1986. Edgar T. F., Himmelblau D. M.,Lasdon L. S.: Optimization of Chemical Processes, McGraw-Hill, Boston, 2001. L. T. Biegler: New directions for nonlinear process optimization. Current Opinion in Chemical Engineering, vol. 21, pp. 32–40, 2018. Further literature individually. |
|
||
Last update: Kubíček Milan prof. RNDr. CSc. (02.10.2018)
Self-study, consultation, solution of given problem. |
|
||
Last update: Kubíček Milan prof. RNDr. CSc. (02.10.2018)
1. Formulation of the optimization problem.
2. Extrems of functions of real variables - methods of classical analysis.
3. Extrems of functions of real variables - unconstrained extreme, extrem with equality constraints.
4. Extrems of real variable functions - Extrems with inequality constraints.
5. Linear programming.
6. Simplex method.
7. Non-linear programming.
8. Adaptive search methods.
9. Gradient methods.
10. Penalty functions.
11. Fundamentals of dynamic programming.
12. Resource distribution problem.
13. Fundamentals of vector optimization.
14. Construction of a Pareto set. |
|
||
Last update: Borská Lucie RNDr. Ph.D. (16.09.2019)
Mathematics A, B |
|
||
Last update: Borská Lucie RNDr. Ph.D. (16.09.2019)
none |
|
||
Last update: Kubíček Milan prof. RNDr. CSc. (02.10.2018)
Solving the given problem. Written and oral exam. |