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The aim is to give a survey of classic and current optimization methods and to apply them to solving practical and real-world engineering problems. Students will learn to formulate optimization problems, state the requirements and constraints put on solution, transform optimization problem to a correct mathematical form, use adequate numerical algorithms in suitable computational environment (Matlab: Symbolic Math Toolbox, Optimization Toolbox, Microsoft Excel: Solver, etc.) and verify and critically evaluate obtained results.
Last update: Pátková Vlasta (20.04.2018)
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Students will be able to:
Last update: Pátková Vlasta (20.04.2018)
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Vypracování a obhajoba tří samostatných projektů: 0 - 25 bodů Ústní zkouška: 0-75 bodů Celkové bodové hodnocení: 100-90 A, 89-80 B, 79-70 C, 69-60 D, 59-50 E, méně než 50 F. Last update: Mareš Jan (03.10.2023)
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R: Venkataraman P.: Applied Optimization with MATLAB Programming. Wiley, New York 2002, 0-471-34958-5 R: Himmelblau, D. M.: Applied Nonlinear Programming. McGraw-Hill, New York 1972, 0-07-028921-2 A: Rao, S. S.: Engineering Optimization. Theory and Practice. Wiley, New York 1996, 0-471-55034-5 A: Goldberg, D.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, 1989, 0-201-15767-5 Last update: Pátková Vlasta (20.04.2018)
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1. Optimization process, concepts and goals, general scheme and basic elements 2. Classical analytical theory of extremes, non-classical applications 3. Linear programming 4. Simplex method 5. Quadratic programming 6. Non-linear programming, one-dimensional and multidimensional seeking 7. Gradient and non-gradient methods 8. Optimization methods with equality and inequality constraints, multiple criteria decision making. 9. Optimization of multistage processes, dynamical programming, maximum principle 10. Variation calculus 11. Combinatorial optimization, graph optimization methods 12. Discrete optimization, branch and bound method 13. Stochastic optimization, simulated annealing method 14. Genetic algorithm, evolution algorithm, taboo search algorithms Last update: Pátková Vlasta (20.04.2018)
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http://moodle.vscht.cz/course/view.php?id=57 http://www.mathworks.com/products/optimization/ http://www.mathworks.com/products/global-optimization/ http://www.mathworks.com/matlabcentral/fileexchange/index?term=tag%3A%22optimization%22 Last update: Pátková Vlasta (20.04.2018)
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Algorithms and Programming, Mathematics I Last update: Pátková Vlasta (20.04.2018)
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Teaching methods | ||||
Activity | Credits | Hours | ||
Účast na přednáškách | 1 | 28 | ||
Práce na individuálním projektu | 2 | 56 | ||
Příprava na zkoušku a její absolvování | 1 | 28 | ||
Účast na seminářích | 1 | 28 | ||
5 / 5 | 140 / 140 |