Course image Operations Research (Undergraduate)
School of Economics

The module on Operations Research introduces students to mathematical models and techniques used to derive values of variables for a complex organizational system that optimizes the performance of that system. More specifically, it creates the students’ awareness of linear linear programming, transportation and assignment, network, and queuing models. The applications include industrial processes, management systems, road and transport networks, and telecommunication systems. The course content is based on real-world examples and cases to encourage students to develop their attitude and ability to discover and innovate.

By the end of the module, students should be able to:

  1. Interpret results of linear programming (application of linear programming, formulation of linear programming models, simplex method, dual linear programming problem, sensitivity analysis, linear programming with matrix algebra);
  2. Interpret results of transportation and assignment problems;
  3. Apply network optimization models (terminology of networks, shortest-path problem, minimum spanning tree problem, maximum flow problem, minimum cost flow problem, and network simplex method);
  4. Apply dynamic programming techniques (characteristics of dynamic programming problems, deterministic dynamic programming);
  5. Explain queueing theory;
  6. Work with Project Management with PERT/CPM

Course image Macroeconomics II (Undergraduate)
School of Economics

This module is an intermediate level to the theory and practice of macroeconomics. The student should gain a sufficient understanding of macroeconomic theory to understand empirical research and, therefore, give valuable insight into topical issues. Particular reference is made to the relative importance of long-run term growth and macroeconomic policies in the open economy.


Course image Operations Research
School of Economics

  1. This module introduces students to mathematical models and techniques used to derive values of variables for a complex organizational system that optimizes the performance of that system.
  2. More specifically, it creates the students’ awareness of linear, transportation and assignment models, network models, and queuing models. 
  3. The applications include industrial processes, management systems, road and transport networks, and telecommunication systems. 
  4. The module content is based on real-world examples and cases to encourage students to develop their attitude and ability to discover and innovate.