| Course Unit Code | 470-6503/01 |
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| Number of ECTS Credits Allocated | 10 ECTS credits |
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| Type of Course Unit * | Choice-compulsory |
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| Level of Course Unit * | Third Cycle |
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| Year of Study * | |
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| Semester when the Course Unit is delivered | Winter, Summer Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| DOS35 | prof. RNDr. Zdeněk Dostál, DSc. |
| BER95 | doc. Ing. Petr Beremlijski, Ph.D. |
| Summary |
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| Optimization methods are basic tools for improving design and technology. The students will learn about basic optimization problems, conditions of their solvability and correct formulation. Effective algorithms, heuristics and software will be presented in an extent that is useful for the soluving engineering problems. |
| Learning Outcomes of the Course Unit |
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| The student will be able to recognize basic classes of optimization problems and will understand conditions of their solvability and correct formulation. Effective algorithms, heuristics and software will be presented in an extent that is useful for solving engineering problems, so that the student will be able to apply their knowledge to the solution of practical problems. |
| Course Contents |
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| Introduction to the calculus of variations. Linear spaces, functionals and their differentials (Fréchet, Gateaux), etc.. |
| Recommended or Required Reading |
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| Required Reading: |
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M. S: Bazaraa, C. M. Shetty: Nonlinear programming, J. Wiley, New York 1979, ruský překlad Mir Moskva 1982.
J. Nocedal, S. Wright, Numerical Optimization, Springer, New York 2005.
R. Fletcher: Practical Methods of Optimization, John Wiley & sons, Chichester 1997. |
O. Došlý, Základy konvexní analýzy a optimalizace. Masarykova universita, Brno 2005.
V. M. Alexejev a j.: Matematická teorie optimálních procesů, Academia, Praha 1992 (překlad z ruštiny).
R. Fletcher: Practical Methods of Optimization, John Wiley & sons, Chichester 1997. |
| Recommended Reading: |
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D. P. Bertsekas, Nonlinear Programming, Athena Scientific, Belmont 1999.
Z. Dostal, Optimal Quadratic Programming Algorithms: With Applications to Variational Inequalities Springer, New York 2009.
I. Griva, S. G. Nash, A. Sofer, Linear and Nonlinear Optimization, Second Edition, SIAM , Philadelphia 2008.
D. T. Pham and D. Karaboga, Intelligent Optimization Techniques, Springer, London 2000. |
D. P. Bertsekas, Nonlinear Programming, Athena Scientific, Belmont 1999.
Z. Dostal, Optimal Quadratic Programming Algorithms: With Applications to Variational Inequalities Springer, New York 2009.
I. Griva, S. G. Nash, A. Sofer, Linear and Nonlinear Optimization, Second Edition, SIAM , Philadelphia 2008.
D. T. Pham and D. Karaboga, Intelligent Optimization Techniques, Springer, London 2000. |
| Planned learning activities and teaching methods |
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| Lectures, Project work |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Examination | Examination | | |