Universität Wien

040182 SE Research Seminar (MA) (2021W)

Meta- and Matheuristics Optimization

4.00 ECTS (3.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
ON-SITE

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. 18 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Schedule:
5.10. Course Outline, Introduction, The Generalized Assignment Problem, Exact Solution Techniques
12.10. Online-Test, Single Solution Metaheuristics
19.10. Online-Test, Population Based Metaheuristics
09.11. Online-Test, Matheuristics - Diving Heuristics, Very Large Neighborhood Search
16.11. Online-Test, Matheuristics – Decomposition Based Heuristics
23.11. Online-Test, Corridor Method, Beam Search, Kernel Search
30.11. Online-Test, Paper Assignment, How to write a seminar paper.
December: Status Update/Pseudocodes/Numerical Study

25.1.: 8.30-13.30 Seminar Presentations

Tuesday 05.10. 09:45 - 11:15 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 05.10. 11:30 - 13:00 Hörsaal 7 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 12.10. 09:50 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 12.10. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 19.10. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 19.10. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 09.11. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 09.11. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 16.11. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 16.11. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 23.11. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 23.11. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 30.11. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 30.11. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 07.12. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 07.12. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 14.12. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 14.12. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 11.01. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 11.01. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 18.01. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 18.01. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 25.01. 09:45 - 11:15 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 25.01. 11:30 - 13:00 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

Aims:
The students will know the state-of-the art methods and design decisions in matheuristic optimization techniques for combinatorial optimization problems (especially in the field of business administration). They will be able to design and develop prototypical solution techniques for standard problems well known in the literature.

Methods:
Students will work in teams on dedicated research topics; the students have to prepare a seminar paper, give a seminar presentation and reimplement a standard matheuristic search technique. A hybrid variant of existing state-of-the art methods should be developed, implemented and tested. In the first part of the semester the basic concepts or matheuristic search techniques are introduced. In the second part of the semester the students have to prepare a seminar paper and presentation (including a state-of-the art review, a reimplementation and hybridization of standard methods and a numerical analysis on standard benchmark instances). The students have to report the progress of their work in a weekly progress report or in a personal meeting.

Content:
Exact Solution Techniques, Single Solution Metaheuristics, Population Based Metaheuristics, Matheuristics - Diving Heuristics, Very Large Neighborhood Search, Decomposition Based Heuristics, Corridor Method, Beam Search, Kernel Search

Assessment and permitted materials

• Short Online Tests
• Seminar Paper
• Presentations at the end of the semester (in teams)

Minimum requirements and assessment criteria

Seminar Paper 30%
Implementation 25%
Präsentation 25 %
Online Tests 20 %

Examination topics

Contents of the course as well as the literature announced in the course

Reading list

Vittorio Maniezzo, Marco Antonio Boschetti, Thomas Stützle: Matheuristics – Algorithms and Implementations, Euro Advanced Tutorials on Operational Research, Springer: Cham, 2021.
Abraham Duarte, Manuel Laguna, Rafael Marti: Metaheuristics for Business Analytics, A Decision Modeling Approach, Euro Advanced Tutorials on Operational Research, Springer: Cham, 2018.

Association in the course directory

Last modified: We 27.09.2023 00:10