Optimization methods

Course title:

Optimization methods

Course code:




In-class hours



Laboratory work/Tutorials:


Self-preparation hours

Practical training:




Total hours:




Study cycle:

BSc, Master, PhD


Winter, summer


Faculty of Economics

Name of the lecturer(s):

Assoc. Prof. Velika Kuneva, PhD

Mode of delivery:

Face-to-face, distance learning



Learning outcomes of the course unit:

The purpose of the Optimization methods 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. The aim of the course is to give knowledge about methods, techniques and approaches to objective optimization. Such knowledge would be useful to everyone who want to solve optimization problems. The course is useful for engineers, economists, Decision Makers in managing companies and production processes, experts in zoning, resource allocation, political sectional distribution population and all other is experts who solve real optimization problems in their activities.

Course contents:

1. Mathematical models.

2. Graphic method.

3. Simplex method.

4. M-method.

5. Duality.

6.  Models and examples in mathematical optimization. Transportation problem.

7. Leontiev’s model.

8. 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