Universität Wien

040676 KU Metaheuristics (MA) (2016W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

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).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 06.10. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 13.10. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 20.10. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 27.10. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 03.11. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 10.11. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 17.11. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 24.11. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 01.12. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 15.12. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 12.01. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 19.01. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 26.01. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß

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

Five short written tests, no material allowed (total of 40 points)
Project work: programming a metaheuristic for an optimisation problem, including written report (40 points)
Oral presentation of the project (20 points)

Minimum requirements and assessment criteria

Students must be able to program. There is relative freedom in the choice of the programming language.

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

Association in the course directory

Last modified: Mo 07.09.2020 15:29