Course INFO 214 · Year II · Summer 2025-2026

OPTIMIZATION TECHNIQUES

Compulsory course in Computer Science, taught by Mihaela Aldea.

This course page is from 2025-2026 and is archived.
See this course for the current academic year

Overview

Lecturer
Mihaela Aldea
Seminar tutor
Mihaela Aldea
Type of course
Compulsory
Language of instruction
Romanian
Erasmus language
English
Domain
Computer Science
Field of study
Computer Science
Form of education
Full-time
Form of instruction
Class
Credit awarded by
Grade
Teaching methods
Lecture, conversation, exemplification.
Entry requirements
Linear Algebra

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 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.

Learning outcomes

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

Assessment

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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