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040676 PR KFK PM/SCM/TL: Praktikum Metaheuristics I (2011W)
Prüfungsimmanente Lehrveranstaltung
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Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 05.09.2011 09:00 bis Mi 21.09.2011 17:00
- Anmeldung von Di 27.09.2011 09:00 bis Mi 28.09.2011 17:00
- Abmeldung bis Fr 14.10.2011 23:59
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine
Zur Zeit sind keine Termine bekannt.
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. The course is divided into 9 chapters. The first chapter introduces fundamental concepts of complexity theory that are key to understand the need for approximate approaches and to design efficient heuristics and metaheuristics. Chapters 2 to 6 discuss classical and modern frameworks for designing heuristics and metaheuristics and Chapters 7 and 9 tackle implementation and testing aspects of heuristics and metaheuristics. Finally, Chapter 8 presents two study cases of how metaheuristics embedded into decision support systems have improved decision making in two companies.
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 workshops 2 and 3, 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: at the end of chapters 2 and 3, 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: students will pass a written test about the theoretical part of the course on 11/15/2011. The test lasts 1h30.
2. [30%] Homework: at the end of chapters 2 and 3, 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: students will pass a written test about the theoretical part of the course on 11/15/2011. The test lasts 1h30.
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.
* in workshops 2 and 3, students will work at the lab on their own during the scheduled time. The lecturer will them during the last two hours to provide individual advise to the groups (30min per group)
* in workshops 2 and 3, students will work at the lab on their own during the scheduled time. The lecturer will them during the last two hours to provide individual advise to the groups (30min per group)
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