After successful completion of the course, students are able to

• discuss and apply basic contents of mathematical programming
•  computer-assisted modeling and analysis of decision problems (partly exact, partly heuristic)
•  Computer-aided planning and optimization of business processes
• outline complexity of mathematical programming and assess the usefulness of heuristic optimization methods

Modelling languages (e.g. General Algebraic Modelling System GAMS), optimization solvers, mathamatical optimization algoriithms, complexity, meta-heuristics, stochastic optimization.

 Students achieve the learning outcomes:  

• through active participation in the online TUWEL lecture parts
• by working through / self-study of the presentation slides, documents and sample coding,
• by partly under guidance and partly independent modeling and implementation of training projects and
• by discussing the results with colleagues via TUWEL.

It is expected that students bring computers (operating system Windows, Mac OS, Linux) into the laboratory exercises. Software (GAMS, possibly MS Excel) is provided cheaply via student software (TU Wien Studentensoftware).

First meeting at Tue Oct 6, 2020, 9 a.m. online.

In the winter semester 2020/21, this course will only take place online (we will definitely never meet in the seminar room).

The students realize explanatory, illustrative and in-depth examples partly under guidance and partly independently; the preparation of the examples together with tests (online) on the basic contents of the VU forms the basis of the assessment.

Urmila Diwekar, Introduction to Applied Optimization, Second Edition, Springer ISBN 978-0-387-76635-5