Course Details
Applications of mathematical methods in economics
DA67 course is part of 22 study plans
Ph.D. full-t. program nD > PST compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program nD > FMI compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program nD > KDS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program nD > MGS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program nD > VHS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDK > PST compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDK > KDS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDK > VHS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDK > FMI compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDK > MGS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program nDA > PST compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program nDA > FMI compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program nDA > KDS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program nDA > MGS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program nDA > VHS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDKA > PST compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDKA > FMI compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDKA > KDS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDKA > MGS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program nDKA > VHS compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. full-t. program I > GAK compulsory-elective Winter Semester 2nd year 10 credits
Ph.D. combi. program IK > GAK compulsory-elective Winter Semester 2nd year 10 credits
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
Prerequisites
Základní znalosti z teorie množin a zběhlost v manipulaci se symbolickými hodnotami.
Planned educational activities and teaching methods
Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.
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.
Specification of controlled instruction, the form of instruction, and the form of compensation of the absences
Vymezení kontrolované výuky a způsob jejího provádění stanoví každoročně aktualizovaná vyhláška garanta předmětu.
Lecture
3 hours/week, 13 weeks, elective
Syllabus of lectures
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.