040676 PR KFK PM/SCM/TL: Practical Course Metaheuristics I (2012W)
Continuous assessment of course work
Labels
Prüfung: 06.12.2012 13:00 Uhr Lab 3
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Th 06.09.2012 09:00 to Th 20.09.2012 14:00
- Registration is open from We 26.09.2012 10:00 to Th 27.09.2012 17:00
- Deregistration possible until Su 14.10.2012 23:59
Details
max. 30 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Thursday
04.10.
13:00 - 18:00
EDV-Labor 3
Thursday
11.10.
13:00 - 18:00
EDV-Labor 3
Thursday
18.10.
13:00 - 18:00
EDV-Labor 6
Thursday
25.10.
13:00 - 18:00
EDV-Labor 3
Information
Aims, contents and method of the course
Despite the recent advances in mathematical programming-based methods and solvers, approximate approaches (heuristics and metaheuristics) are still the optimization-based technology that is most widely used to support decision making in practice. The objective of this course is to provide students with the fundamental tools for designing, tuning, and testing heuristics and metaheuristics for hard combinatorial optimization problems. Besides that, we will also cover the fundamental concepts of complexity theory that are the key to understand the need for approximate approaches and to design efficient heuristics and metaheuristics.
Assessment and permitted materials
1. [40%] Course project: implementing a simple metaheuristic for a combinatorial optimization problem. The project will be developed in groups of 2 students. The groups will start and advance on their project during two workshops, and then complete it on their own before handing it in to the lecturer for grading. Further details on the deliverables of the project will be provided in class.
2. [30%] Homework: a homework consisting in designing components of a (meta)heuristic for a given combinatorial optimization problem will be handed out to the students. Students will have to do a short oral report (<5min) on their solutions to the homework. Further details will be announced in class.
3. [30%] Written test (1h30): students will pass a written test about the theoretical part of the course.
2. [30%] Homework: a homework consisting in designing components of a (meta)heuristic for a given combinatorial optimization problem will be handed out to the students. Students will have to do a short oral report (<5min) on their solutions to the homework. Further details will be announced in class.
3. [30%] Written test (1h30): students will pass a written test about the theoretical part of the course.
Minimum requirements and assessment criteria
At the end of the course, students will know the fundamental of designing, tuning, and testing heuristics and metaheuristics for hard combinatorial optimization problems.
Examination topics
Reading list
[1] Handbook of Metaheuristics 2nd edition. Gendreau, M. & Potvin, J.-Y. (Eds.).Springer, ISBN 978-1-4419-1663-1
[2] Stochastic Local Search, Foundations and Applications. Hoos, H. & Stützle, T. Elsevier, ISBN 1-55860-872-9
[3] Search Methodologies, Introductory tutorials in optimization and decision support techniques. Burke, E. K. & Kendall, G. Springer, ISBN 0-387-23460-8
[2] Stochastic Local Search, Foundations and Applications. Hoos, H. & Stützle, T. Elsevier, ISBN 1-55860-872-9
[3] Search Methodologies, Introductory tutorials in optimization and decision support techniques. Burke, E. K. & Kendall, G. Springer, ISBN 0-387-23460-8
Association in the course directory
Last modified: Mo 07.09.2020 15:29