Title Algorithms and Combinatorial Optimization
Lesson Code 321-10000
Semester 9
ECTS 5
Hours (Theory) 3
Hours (Lab) 0
Faculty Kaporis Alexis

Syllabus

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. Exploiting the limitations of these techniques and case study of resent developments. Dynamic programming and 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.

Prerequisite Courses

Not required.

Basic Textbooks

Combinatorial optimization: algorithms and complexity. C. Papadimitriou, K. Steiglitz

Combinatorial Optimization
Polyhedra and Efficiency. Schrijver, Alexander

Additional References

Journal of combinatorial optimization

Teaching and Learning Methods

 

Activity Semester workload
Lectures 39 hours

 
Personal study 83 hours
 
Final exams 3 hours
Course total 125 hours (5 ECTS)

Student Performance Evaluation

Work in classroom. Final exams.

Language of Instruction and Examinations

Greek, English (for Erasmus students)

Delivery Mode

With attendance in classroom, and watching online video lectures