040676 PR KFK PM/SCM/TL: Praktikum Metaheuristics I (2012W)
Prüfungsimmanente Lehrveranstaltung
Labels
Prüfung: 06.12.2012 13:00 Uhr Lab 3
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Do 06.09.2012 09:00 bis Do 20.09.2012 14:00
- Anmeldung von Mi 26.09.2012 10:00 bis Do 27.09.2012 17:00
- Abmeldung bis So 14.10.2012 23:59
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Donnerstag 04.10. 13:00 - 18:00 EDV-Labor 3
- Donnerstag 11.10. 13:00 - 18:00 EDV-Labor 3
- Donnerstag 18.10. 13:00 - 18:00 EDV-Labor 6
- Donnerstag 25.10. 13:00 - 18:00 EDV-Labor 3
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
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.
Art der Leistungskontrolle und erlaubte Hilfsmittel
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.
Mindestanforderungen und Beurteilungsmaßstab
At the end of the course, students will know the fundamental of designing, tuning, and testing heuristics and metaheuristics for hard combinatorial optimization problems.
Prüfungsstoff
Literatur
[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
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 07.09.2020 15:29