Course Details
Applications of mathematical methods in economics
Academic Year 2022/23
DA67 course is part of 23 study plans
unknown (history data) unknown (history data) 1st year
D-K-E-SI (N) Winter Semester 1st year
D-K-E-SI (N) Winter Semester 1st year
D-K-E-SI (N) Winter Semester 1st year
D-K-E-SI (N) Winter Semester 1st year
D-K-E-SI (N) Winter Semester 1st year
D-K-C-SI (N) Winter Semester 1st year
D-K-C-SI (N) Winter Semester 1st year
D-K-C-SI (N) Winter Semester 1st year
D-K-C-SI (N) Winter Semester 1st year
D-K-C-SI (N) Winter Semester 1st year
D-P-E-SI (N) Winter Semester 1st year
D-P-E-SI (N) Winter Semester 1st year
D-P-E-SI (N) Winter Semester 1st year
D-P-E-SI (N) Winter Semester 1st year
D-P-E-SI (N) Winter Semester 1st year
D-P-C-SI (N) Winter Semester 1st year
D-P-C-SI (N) Winter Semester 1st year
D-P-C-SI (N) Winter Semester 1st year
D-P-C-SI (N) Winter Semester 1st year
D-P-C-SI (N) Winter Semester 1st year
D-P-C-GK Winter Semester 1st year
D-K-C-GK Winter Semester 1st year
Basics of graph theory, finding optimum graph solutions.
Finding the cheapest spanning tree of a graph.
Finding the shortest path in a graph.
Determining the maximum flow in a network.
NP-complete problems.
Travelling salesman problem.
Linear programming.
Transport prpoblem.
Integer programming.
Basics of the theory of games.
Course Guarantor
Institute
Objective
After the course, the students should be familiar with the basics of the theory of graphs necessary to formulate combinatorial problems on graphs. They should know how to solve the most frequently occurring problems using efficient algorithms. They will know about some heuristic approaches to intractable problems. They will learn the basics of linear programming and the theory of games and their applications in business.
Syllabus
1. Basics of graph theory I
2. Basics of graph theory II.
3. Finding the minimum soanning tree in a graph.
4. Finding the shortest path in a graph.
5. Determining a maximum flow in a network I.
6. Determining a maximum flow in a network II.
7. NP-complete problems.
8. Travelling salesman problem.
9. Travelling salesman problem, heuristic methods.
10. Linear programming, theoretical basis.
11. Simplex metoda.
12. Integer programming.
13. Matrix games, solutions in mixed strategies.
Prerequisites
Základní znalosti z teorie množin a zběhlost v manipulaci se symbolickými hodnotami.
Language of instruction
Czech
Credits
10 credits
Semester
summer
Forms and criteria of assessment
examination
Specification of controlled instruction, the form of instruction, and the form of compensation of the absences
Extent and forms are specified by guarantor’s regulation updated for every academic year.
Offered to foreign students
Not to offer
Course on BUT site
Lecture
13 weeks, 3 hours/week, elective
Syllabus
1. Basics of graph theory I
2. Basics of graph theory II.
3. Finding the minimum soanning tree in a graph.
4. Finding the shortest path in a graph.
5. Determining a maximum flow in a network I.
6. Determining a maximum flow in a network II.
7. NP-complete problems.
8. Travelling salesman problem.
9. Travelling salesman problem, heuristic methods.
10. Linear programming, theoretical basis.
11. Simplex metoda.
12. Integer programming.
13. Matrix games, solutions in mixed strategies.