Universität Wien

040134 UK Optimization in Mathematics (2023S)

10.00 ECTS (5.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
MIXED

Dieser Kurs ist primär für Studierende der VWL vorgesehen.

Voraussetzungen: BW- und IBW-Studierende müssen VO und UE Mathematik 1 bereits absolviert haben, VWL-Studierenden wird der vorherige Besuch dieser LVen dringend empfohlen.

Zum UK gibt es eine Fragestunde (Chiara Valentin): Termine tba

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. 120 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

Wednesday 01.03. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 06.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Monday 06.03. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday 08.03. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday 15.03. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 20.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Monday 20.03. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday 22.03. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 27.03. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Monday 27.03. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday 29.03. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 17.04. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Monday 17.04. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday 19.04. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 24.04. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Monday 24.04. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday 26.04. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Tuesday 02.05. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday 03.05. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 08.05. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Monday 15.05. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Tuesday 16.05. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday 17.05. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 22.05. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Tuesday 23.05. 09:00 - 10:30 Digital
Wednesday 24.05. 08:00 - 09:30 Digital
Wednesday 31.05. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Thursday 01.06. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Monday 05.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Monday 12.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Tuesday 13.06. 08:00 - 09:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 13.06. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Saturday 17.06. 09:45 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 19.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00
Tuesday 20.06. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Wednesday 21.06. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 26.06. 09:45 - 13:00 Seminarraum 5, Kolingasse 14-16, EG00

Information

Aims, contents and method of the course

The course covers two main topics. The first topic is multi-dimensional analysis: concepts that are known from Mathematics 1 will be generalized to functions with more than one variable. The second topic is optimization. Here we see methods how multivariate functions can be optimized. The multidimensional differential calculus will be an important tool. Optimization will be studied without and with constraints (in the form of equalities or inequalities).
All these topics play an important role in microeconomics and all fields of economics using microeconomic ideas.

Detailed list of topics:

1. Multidimensional Analysis
Gradients
Jakobi-Matrices
Hesse Matrix
Inverse Function Theorem
Implicit Function Theorem
2. Optimization
Unconstrained
Inequality constraints
Equality constraints

The lectures take place partly in digital form and partly in presence in a lecture room. See the detailed list of dates above.

About the exercise session:
We will stick to the following procedure

- For every session students will be asked to prepare examples, which will be announced via Moodle.

- Students have to earn points by presenting their solutions on the blackboard.

- People may volunteer to present. In case of multiple volunteers a random choice among them is made.

- In order to pass the course, one such presentation must be given. In addition the first presentation earns students 4 points for their overall grading. A possible second presentation will earn them 2 additional points.

- The session lasts 3 hours. Students will be divided into 3 groups, which will be lectured separately in one hour slots.

Assessment and permitted materials

- Presentation of homework examples in class
- 2 Tests (open book, digital)
Dates of tests:
Midterm: MO, 8.5.23, 11:30 - 13 Uhr
Endterm: MO, 26.6.23, 11:30 - 13 Uhr

Minimum requirements and assessment criteria

Grading is based on:
- Midterm-Test (max. 48 Points)
- Endterm-Test (max. 48 Points)
- Presentation of homework: 4 points for the first (mandatory), 2 for a second (optional), which adds up to a maximum of 6 points per person.

Requirement passing the course:
- The sum of all points earned must be greater of equal to 51.
- One presentation of a homework exercise must be given.
- One of the two test scores must be greater of equal to 24 points.

Brackets for grades:
Assuming all criteria for a positive evaluation are met, you will be graded according to the following table, where X is the sum of points you earned:
90<= X 1
76<= X <90 2
64<= X <76 3
51<= X <64 4
X <51 5

Examination topics

Content of the lecture and the exercises

Reading list

Immanuel Bomze : Mathematische Optimierung - Skriptum zum UK im BA-Studium VWL.
Erhältlich im Facultas-Shop, Erdgeschoss OMP1.

Association in the course directory

Last modified: Mo 05.06.2023 15:07