Mathematical programming
Course title: |
Mathematical programming |
|
Course code: |
IFMPR |
|
ECTS: |
5 |
|
In-class hours |
Lectures: |
30 |
Laboratory work/Tutorials: |
30 |
|
Self-preparation hours |
Practical training: |
- |
Other: |
- |
|
Total hours: |
60 |
|
Language: |
English |
|
Study cycle: |
BSc, Master, PhD |
|
Semester: |
Winter, summer |
|
Faculty: |
Faculty of Economics |
|
Name of the lecturer(s): |
Assoc. Prof. Velika Kuneva, PhD |
|
Mode of delivery: |
Face-to-face, distance learning |
|
Prerequisites: |
no |
|
Learning outcomes of the course unit: |
The purpose of this Mathematical Programming course is to make students familiar with the optimization problems in economics, which can be successfully resolved and analyzed by means of mathematics. The course contains not only theoretical knowledge but also provides the opportunity to develop problem-solving skills. The students are introduced to mathematical models of basic optimization problems, the methods of linear programming- simplex and M-method, integer programming, duality. In addition, the algorithm for solving the so-called “transportation problem” is being reviewed. Attention is paid to the economic interpretation of the solutions with the view of using them to select an appropriate management strategy. |
|
Course contents: |
1. Graphic method. 2. Simplex method. 3. M-method. 4. Duality. 5. Integer programming 6. Models and examples in mathematical optimization-Transportation problem. 7. Linear programming using Microsoft Excel Solver. |
|
Recommended or required reading: |
1. Dantrig, D. Linear Programming and Extensions. Princebon Berkeley, University Press, 1963. 2. MacDonald, Z. Teaching. Linear Programming using Microsoft Excel Solver. The Virtual Edition, vol. 9, lssue 3, 1995. |
|
Planned learning activities and teaching methods: |
Lectures, presentations, briefing, tutorials, conversation, discussions, brainstorming |
|
Assessment methods and criteria: |
Exercises evaluation, Written exam |