Czech

Not applicable.

Fundamental concepts, methods and analytical techniques related to decision making models including risk elements will be studied. Specific ways of reasoning, typical for decision making under uncertainty and risk will be developed and enhanced.

Basic knowledge of Calculus techniques; elementary knowledge of windows based applied software. The course content is linked to 2SAMZ course taught in the previous semester.

Not applicable.

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Course-unit credit requirements: active participation in seminars, mastering the subject matter, and delivery of semester assignment. Examination (written form): a practical part (4 tasks), a theoretical part (4 tasks); ECTS evaluation used.

1. Selected deterministic models: linear and nonlinear optimization.
2. Selected models of multicriteria optimization and decision making.
3. Selected engineering optimization models: inverse problems.
4. Selected deterministic, stochastic, and heuristic solution improving methods.
5. Selected decision making models - software for optimization
6. Decision making models under risk and uncertainty - deterministic reformulations and their properties.
7. Decision making models under risk and uncertainty - engineering applications.
8. Decision making models under risk and uncertainty - discrete mathematics applications.
9. Selected stochastic decision making models for network flows.
10. Multistage models and dynamic programming.
11. Dynamic models - scenario-based techniques, applications in GAMS.
12. Mathematical modelling of advanced decision making structures.
13. Decision making models for conflicts; model transforamtions and approximations.

Not applicable.

Students will learn useful knowledge of decision making models involving uncertainty and risk. They will also learn how apply studied models and methods in the related application areas.

Attendance at seminars is controlled and the teacher decides on the compensation for absences.

Not applicable.

Not applicable.

GAMS User's Guide, www.gams.com
KLAPKA A KOL.: Metody operačního výzkumu, VUTIUM 2001, ISBN 80-214-1839-7
POPELA, P.: Nonlinear Programming, University of Malta, učební texty ÚM VUT v Brně, 2001.
POPELA, P.: Stochastic Programming, University of Malta, učební texty ÚM VUT v Brně, 2003.

KALL, P., WALLACE, S.W.: Stochastic Programming, Wiley 1993, ISBN 0471951080
MINOUX, M.: Mathematical Programming, Wiley, 1988, ISBN 0471901709
WILLIAMS, H. P.: Model Building in Mathematical Programming, Wiley 1993, ISBN 0471941115.