Course aims:

First, discipline aims, learning to analyze and decide logically and rigorously.
On the other hand, it contributes to a multidisciplinary preparation of future IT specialists, aiming in this way to familiarize students with the concepts and techniques of mathematical modeling of social and economic phenomena.
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Course Entry Requirements:

Linear Algebra

Course contents:

1. Solving a linear programming problem by graphical and algebraic methods\ 2. Simplex method for solving linear programming problems 3. Duality. The dual simplex algorithm 4. Reoptimization of linear programming problems 5. Parametric linear programming 6. Transport problems. 7. Reoptimization of transport problems. 8. Parametric transport problems. 9. Special transport problem. 10. Integer linear programming – Gomory methods 11. Dantzig-Manne algorithm for solving integer linear programming problems. 12. Bellman method 13. Enumeration and evaluation methods.

Teaching methods:

Lecture, conversation, exemplification.

Learning outcomes:

Knowing the mathematical basic elements of optimization algorithms, familiarity with the use of optimization techniques and algorithms to solve problems.

Learning outcomes verification and assessment criteria:

Written paper – 50%; continuous assessment – 50%.

Recommended reading:

• G. David – Linear and Non Linear Programming, Addison Wesley, Massachusetts, 1989.
• G. L. Nemhauser, L. A. Wolsey – Integer and combinatorial optimization, John Wiley & Sons Inc, New York, 1999.
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