This course begins with introduction of the subject of operational research (management science), methods of which are applicable to solve problems in a number of areas. It continuous with the principles of the creating models, as well as with the construction of enterprise balance models, the statistical methods important for the comprehension of operational research methods are presented. Methods of linear programming useful in solving various problems are studied in depth, as well as methods of integer, nonlinear, stochastic and dynamic programming. To evaluate the effectiveness, productivity and efficiency of units is used a method based on linear programming - data envelopment analysis (DEA). In addition, students learn to apply the methods of game theory, which deal with the solution of conflict situations in which interests of two or more players are collided. There multicriteria methods of decision making under certainty, uncertainty and risk are also treated. Furthermore, the course deepens students' knowledge of inventory models, queuing theory models, Industrial replacement and maintenance models and simulation models. The course follows and broaden the bachelor course: Statistical and decision analysis.

Submission of solved problem tasks and its interpretation. Examination of the following topics:

1.Introduction to operational research, process model creation

2.Enterprise balance models (structural analysis)

3.Probabilistic models of discrete and continuous random variables

4.Linear programming: problem formulation, graphical solution, simplex method

5.Linear programming: duality, sensitivity analysis, solving different problems (capacity problems, transportations problem)

6.Integer, non-linear and dynamic programming

7.Data envelopment analysis

8.Combinatorial models

9.Theory of games

10.Multi-criteria decision making under certainty, uncertainty and risk

11.Theory of inventory management, queuing theory models,

12. Industrial replacement and maintenance models

13. Simulation models

1.Introduction to operational research, process model creation

2.Enterprise balance models (structural analysis)

3.Probabilistic models of discrete and continuous random variables

4.Linear programming: problem formulation, graphical solution, simplex method

5.Linear programming: duality, sensitivity analysis, solving different problems (capacity problems, transportations problem)

6.Integer, non-linear and dynamic programming

7.Data envelopment analysis

8.Combinatorial models

9.Theory of games

10.Multi-criteria decision making under certainty, uncertainty and risk

11.Theory of inventory management, queuing theory models,

12. Industrial replacement and maintenance models

13. Simulation models

1.Introduction to operational research, process model creation

2.Enterprise balance models (structural analysis)

3.Probabilistic models of discrete and continuous random variables

4.Linear programming: problem formulation, graphical solution, simplex method

5.Linear programming: duality, sensitivity analysis, solving different problems (capacity problems, transportations problem)

6.Integer, non-linear and dynamic programming

7.Data envelopment analysis

8.Combinatorial models

9.Theory of games

10.Multi-criteria decision making under certainty, uncertainty and risk

11.Theory of inventory management, queuing theory models,

12. Industrial replacement and maintenance models

13. Simulation models

The aim of the course is to teach students to apply quantitative methods of operational research in systems analysis and solution of technical-managerial decision problems.

Kožíšek, J., Stieberová, B.: Statistická a rozhodovací analýza, VČVUT, Praha 2014

Gros, I.: Kvantitativní metody v manažerském rozhodování, Grada, Praha, 2003

Jablonský, J.: Operační výzkum, Professional Publishing, Praha 2007

Frederick S. Hillier & Gerald J. Lieberman, Introduction to Operations Research, McGraw-Hill: Boston MA; 10th Edition, 2014