052312 VO Computational Optimisation (2021W)
Labels
REMOTE
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
Language: English
Examination dates
Monday
31.01.2022
18:30 - 20:00
Digital
Monday
16.05.2022
10:00 - 11:30
Digital
Monday
27.06.2022
10:00 - 11:30
Digital
Lecturers
Classes (iCal) - next class is marked with N
The lecture will take place partially in presence and remote. Detailed information will be published in Moodle.
Monday
04.10.
18:30 - 20:45
Digital
Monday
11.10.
18:30 - 20:45
Digital
Monday
18.10.
18:30 - 20:45
Digital
Monday
25.10.
18:30 - 20:45
Digital
Monday
08.11.
18:30 - 20:45
Digital
Monday
15.11.
18:30 - 20:45
Digital
Monday
22.11.
18:30 - 20:45
Digital
Monday
29.11.
18:30 - 20:45
Digital
Monday
06.12.
18:30 - 20:45
Digital
Monday
13.12.
18:30 - 20:45
Digital
Monday
10.01.
18:30 - 20:45
Digital
Monday
17.01.
18:30 - 20:45
Digital
Monday
24.01.
18:30 - 20:45
Digital
Information
Aims, contents and method of the course
Assessment and permitted materials
Oral exam after the semester (presumably online). Four "Sammeltermine" will be announced, candidates should register to one of them.
Minimum requirements and assessment criteria
At least half of the questions at the exam must be correctly answered to pass the course.
Examination topics
For each of the two parts of the course (each given by one of the two lecturers), slides will be made available to the participants. The content of these slides defines the topics of the exam.
Reading list
Any introductory textbook on integer programming/combinatorial optimization should cover most/all of the topics.
Association in the course directory
Module: SWI STW CO
Last modified: Fr 12.05.2023 00:13
Topics addressed include:
- Mathematical Programming
- Discussion of various classical discrete optimization problems (facility location, traveling salesperson, ...)
- Theory of NP-completeness
- Metaheuristics
- Problems on Graphs and Networks (Maximum Flow, Spanning/Steiner tree and variants)
- Nonlinear Optimization Methods (e.g., Frank-Wolfe Method)This course is done as lecture; there is an accompanying exercise-part as an own course, students are encouraged to take both courses in the same semester.Due to the current Covid-19 situation, the course will presumably be given in digital form (online via MS Teams, at the times assigned to the course). Switches between physical and digital presentation will be announced to the participants in time.