The course is intended for persons interested in studying techniques with large practical usefulness. Since there are only few theoretical results available for these methods, we will not focus on theory but rather on gaining practical experience with the methods.
Expected learning outcome
After the course, the student is expected to be able to:
- describe in a precise and suitable language, including with the
help of pseudeocode, the algorithms from the curriculum;
- adapt specific algorithms (construction heuristics and local
search) to special cases of the problems studied or to new problems;
- design new algorithms based on the principles of those learned in the course;
- implement the designed algorithms in a suitable programming language;
- analyze the applied heuristic algorithms with respect to solution
quality, computation time, memory usage and other qualities;
- undertake empirical studies of the applied methods and draw sound
conclusions on qualitative and quantitative aspects of these methods;
- discuss the results obtained in the two previous points.
Subject overview
Construction heuristics, greedy heuristics, local search, iterative improvement. Several optimization problems, including the travelling salesman problem, satisfiability, and graph coloring.
Literature
Re-examination following the curriculum.
Expected working hours
The teaching method is based on three phase model.
Forelæsninger: 20 timer
Laboratorieøvelser: 14 timer
Educational activities
Language
This course is taught in Danish or English, depending on the lecturer. However, if international students participate, the teaching language will always be English.
Course enrollment
See deadline of enrolment.
Tuition fees for single courses
See fees for single courses.