Here you will find the lectures offered by our working group in the current semester.
If you would like to attend a seminar, a proseminar or a reading course during the winter semester, please contact the supervisor or the use URM. Appointments are then determined in consultation with the participants.
Lectures in Summer Term
Following lectures are offered during summer term 2019 by our working group:
Nonlinear optimization problems are optimization problems where the objective function and / or constraints are nonlinear. Such problems that arise in a variety of applications can not be solved by methods known from linear optimization. This lecture covers theoretical background and algorithmic approaches to solve nonlinear optimization problems, both with and without constraints.
Among other things, the following topics are covered:
- one-dimensional and multi-dimensional search
- Newton and Quasi-Newton procedures
- Convex analysis and separation theorems
- Optimality conditions for convex problems
- Optimality conditions for general problems
- Penalty- and barrier-methods
Optimization in Public Transport
In this lecture we will discuss the basics of mathematical public transport planning. The goal is to construct a public transport plan that is attractive for both passengers and operators. We will discuss and model the corresponding problems as well as specific solution methods. The covered topics include:
- network design
- line planning
- vehicle scheduling
- disposition management
Reading courses, seminars und proseminars
Following supplementing courses are offered during summer term 2019 by our working group:
We will read and discuss selected literature on the following topics:
- Multicriteria Optimization
- Location Theory
- Network Flows
- Combinatorial and Discrete Optimization
The aim is to gain a basic overview of current research topics. In this respect, the Reading Course prepares for a master's thesis in these subject areas.
Reading Course Games on Networks
Many game-theoretic problems are based on a network structure that can be given, for example, by identifying the players with the nodes of a (directed or undirected) graph. In this reading course, we will use original research articles to obtain an overview of different types of such games on networks and of different methods for their analysis. Special emphasis will be put on methods from (algorithmic) mechanism design.
Seminar Optimization in Health Care
Hospitals and other healthcare facilities naturally experience mathematical optimization problems in many places. Examples include creating staff rosters or assigning patients to beds within a hospital. The solutions found to these problems often have far-reaching effects on the efficiency of the clinic operation and employee satisfaction. However, due to complex conditions and multiple, sometimes conflicting objectives, good solutions can rarely be found using manual planning methods, which provides a strong motivation for using mathematical optimization models in healthcare. In this seminar, we will use original sources to work out different questions in the field of optimization in the healthcare system and the methods used to solve them. In addition to the pure transfer of knowledge on the subject a variety of other skills to be acquired and skills are trained, e.g., techniques for the efficient reading of mathematical texts, the technical dialogue, dealing with the English language, presentation skills, the writing of short excerpts to mathematical content or about the use of LaTeX.
Lectures for students of other subjects
Following courses are offered for students of other subjects during summer term 2019 by our working group:
Mathematics for computer scientists: analysis
- Development of basic concepts, theorems and methods of differential and integral calculus.
- The lecture includes i.a. the following topics:
Basic constructions and basic knowledge: sets, elementary proof methods, complete induction, relations, maps, drawer principle, equivalence relations, natural numbers, integers, rational numbers;
Fundamentals of Analysis: convergence of sequences and series, real and complex numbers, functions, continuity, differentiability, extreme value problems, integral calculus;
Perspective on Multivariate Analysis: partial derivatives, Taylor Formulas, local extrema; application of the treated mathematical tools to problems in computer science