SubjectsSubjects(version: 808)
Course, academic year 2017/2018
Engineering Optimization - N445061
Czech title: Inženýrská optimalizace
Guaranteed by: Department of Computing and Control Engineering (445)
Actual: from 2013
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 [hours/week]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
For type:  
Additional information:
Guarantor: Mareš Jan doc. Ing. Ph.D.
Hanta Vladimír Ing. CSc.
Aim of the course -
Last update: Hanta Vladimír Ing. CSc. (01.07.2013)

Students will be able to:

  • formulate optimization problems
  • solve basic and advanced optimization tasks in different computing environments
  • use various optimization programs and tools
Last update: Hanta Vladimír Ing. CSc. (01.07.2013)

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

Learning resources -
Last update: Hanta Vladimír Ing. CSc. (01.07.2013)

Last update: Hanta Vladimír Ing. CSc. (22.06.2009)

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

Registration requirements -
Last update: Hanta Vladimír Ing. CSc. (01.07.2013)

Algorithms and Programming, Mathematics I

Class 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
Evaluation of a student
Form Balance
Aktivní účast na výuce 20
Protokoly z individuálních projektů 40
Zkouškový test 20
Ústní zkouška 20