Optimisation

Type of study	Doctoral
Language of instruction	Czech
Code	157-9986/01
Abbreviation	O
Course title	Optimisation
Credits	10
Coordinating department	Department of Systems Engineering and Informatics
Course coordinator	prof. Mgr. Ing. František Zapletal, Ph.D.

Subject syllabus

1) Systemic approach, mathematical modelling.
2) Convex programming
3) Logical constraints
4) Risk measures
5) Single-stage and multi-stage stochastic programming.
6) Multi-stage stochastic programming.
7) Chance-constrained programming
8) Benders decomposition method.
9) Basics of fuzzy logic, algebra and set theory.
10) Possibilistic programming.
11) Flexible programming.
12) Intuitionistic fuzzy sets and their use in optimization.

E-learning

Information are provided to students at the lectures, through the LMS system. In LMS, there is an extended descriptions of the lectures and recommended literature.

Literature

SHAPIRO, Alexander a Andrzej RUSZCZYNSKI, ed. Stochastic programming. Amsterdam: Elsevier, 2003. Handbooks in operations research and management science, v. 10. .
FIEDLER, Miroslav. Linear optimization problems with inexact data. New York: Springer, c2006. ISBN 0-387-32697-9.
PRÉKOPA, András. Stochastic programming. Dordrecht: Kluwer Academic Publishers, c1995. Mathematics and its applications, v. 324. ISBN 0-7923-3482-5.

Advised literature

BIRGE, John R. a François LOUVEAUX. Introduction to stochastic programming. 2nd ed. New York: Springer, c2011. Springer series in operations research. ISBN 978-1-4614-0236-7.
KALL, Peter a János MAYER. Stochastic linear programming: models, theory, and computation. 2nd ed. New York: Springer, c2011. International series in operations research & management science, 156. ISBN 978-1-4419-7728-1.
SAKAWA, Masatoshi, Hitoshi YANO a Ichiro NISHIZAKI. Linear and multiobjective programming with fuzzy stochastic extensions. New York: Springer, c2013. International series in operations research & management science, 203. ISBN 978-1-4614-9398-3.

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