390028 UK Convex Representations and Relaxations for Non-convex Quadratic Optimization (2016W)
Continuous assessment of course work
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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 Mo 12.09.2016 09:00 to Mo 31.10.2016 14:00
- Deregistration possible until Mo 31.10.2016 14:00
Details
max. 50 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Monday 07.11. 08:45 - 11:45 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 08.11. 09:30 - 12:30 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
- Tuesday 08.11. 14:00 - 16:00 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
- Wednesday 09.11. 09:30 - 12:30 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
- Wednesday 09.11. 14:00 - 16:00 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
- Thursday 10.11. 09:30 - 12:30 Seminarraum 6 Oskar-Morgenstern-Platz 1 1.Stock
- Friday 11.11. 09:00 - 13:00 Seminarraum 14 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
We consider convex relaxations for non-convex quadratic optimization that utilize semidefiniteness together with constraints obtained from the Reformulation-Linearization Technique (RLT) and generalizations of RLT. From a theoretical standpoint we show that these relaxations dominate convex relaxations obtained using some alternative methodologies, and also that in certain cases the relaxations in fact give exact representations (that is, they are tight). Computational results show that these convex relaxations usually provide excellent bounds, and for some problem classes are often empirically tight even when they are not provably tight.
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Last modified: Mo 07.09.2020 15:46