Course: Optimization, Theory and Applications

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Course title Optimization, Theory and Applications
Course code KMA/PGSA5
Organizational form of instruction Lecture
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 5
Language of instruction Czech, English
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Machalová Jitka, doc. RNDr. Ph.D., MBA
Course content
1. Optimality conditions, Lagrange multipliers. 2. Convex optimization. 3. Smooth optimization methods. 4. General nonlinear optimization problem. 5. Multicriterial optimization problem. 6. Optimal control problem.

Learning activities and teaching methods
Work with Text (with Book, Textbook)
Learning outcomes
To get an overview about optimization methods and possible applications.
Comprehension Understanding of basic optimization methods.
Prerequisites
Oral exam: to know and to understand the subject.

Assessment methods and criteria
Oral exam

Oral exam: to know and to understand the subject.
Recommended literature
  • Bertsekas, D. (1999). Nonlinear Programming. Second edition. Athena Scientific, Belmont.
  • Ciarlet, P. G. (1989). Introduction to Numerical Linear Algebra and Optimization. Cambridge University Press, Cambridge.
  • Haslinger, J., Mäkinen, R. A. E. (2003). Introduction to Shape Optimization: Theory, Approximation, and Computation. SIAM, Philadelphia.
  • Jahn, J. (2007). Introduction to the Theory of Nonlinear Optimization. Third edition. Springer.
  • Mäkelä, M. M., Neittaanmäki, P. (1992). Nonsmooth Optimization. Analysis and Algorithms with Application to Optimal Control. World Scientific Publ. Co., Singapore.
  • Miettinen, K. M. (1999). Nonlinear Multiobjective Optimization. Kluwer Academic Publ.
  • Strang, G. (1986). Introduction To Applied Mathematics. Wellesley-Cambridge Press.
  • Tröltzsch, F. (2010). Optimal Control of Partial Differential Equations. Theory, Methods and Applications. AMS, Providence, Rhode Island.
  • Tuy, H. (2016). Convex Analysis and Global Optimization. Second edition. Springer.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Applied Mathematics (2020) Category: Mathematics courses - Recommended year of study:-, Recommended semester: -