Algorithms and Combinatorial Optimization
| Course Code | 321-10000 |
|---|---|
| Semester | 9 |
| ECTS | 5.00 |
| Hours (Theory) | 3 |
| Hours (Lab) | |
| Instructor | Kaporis Alexis |
Course Content
Mathematical modeling of combinatorial optimization problems, in the realm of areas such as Biology, Networks, time-dependent processes, resources allocation, game theory, etc. Study of techniques to tackle such problems, as branch and bound, heuristics, probabilistic techniques, linear/convex programming. Exploiting the limitations of these techniques and case study of resent developments. Approximation algorithms, polynomial time approximation schemes. Local search methods, PLS- -completeness, neighborhood structures. Local search methods in the perspective of game theory.
Learning Outcomes
When the student completes the course successfully:
- She will have the knowledge to model as a linear/convex program some of the most important problems of the combinatorial optimization.
- She will have the skills to apply techniques and algorithms that solve linear/convex programs.
- She will have the capability to solve problems of linear/convex programming.
Prerequisites
Not required.
Teaching and Learning Methods
| Activity | Semester workload |
|---|---|
| Lectures | 39 hours |
| Personal study | 83 hours |
| Final exams | 3 hours |
| Course total | 125 hours (5 ECTS) |
Assessment Methods / Grading
Work in classroom. Final exams.
Teaching Language
Greek (English for Erasmus students)