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Discrete Optimization
Last Updated: 2026-06-01 11:33:47
Abstract
This course gives an introduction to discrete optimization problems.A discrete optimization problem is the task to optimize a linear function over the integer points in a polyhedron. This topic is very rich in terms of the underlying theoretical tools that one can use to understand and solve such problems.
Objective
The goal of this course is to obtain an understanding of the theory of discrete optimization that underlies algorithms to solve such problem. Discrete optimization is a rich topic that includes lattice theory, approximation algorithms and polyhedral combinatorics.
Content
Part 1: From linear to integer optimization Linear and Integer optimization problems are strongly related via underlying polyhedra. This is the classical setting of polyhedral combinatorics. Part 2: Binary optimization We study various topics and techniques related to linear problems in variables that can attain values zero or one only. This is the classical setting of approximation algorithms and cutting plane procedures. Part 3: General integer optimization This part is devoted to a study of integer optimization in general integer variables. We will discuss lattice theory and the theory of integral generating sets in cones to understand the subject.
Resources
Lecture Notes
Lecture notes are available
General Information
- Language
- English
- Levels
- BSC , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 120 minutes
- Aids
- None
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Discrete Optimization
on 27 February 2025, 10:15-12:00 in ML J 34.1 (instead of HG E 1.1)
|
|
4 h weekly |
| exercise |
Discrete Optimization
Groups are selected in myStudies.
Tue 16-17 (starting in the second week of the semester)
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|
1 h weekly |
Offered In
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Kernfächer aus Bereichen der angewandten Mathematik ... (vollständiger Titel: Kernfächer aus Bereichen der angewandten Mathematik und weiteren anwendungsorientierten Gebieten)
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Kernfächer (Für das Master-Diplom in Angewandter Mathematik ist die folgende Zusatzbedingung (nicht in myStudies ersichtlich) zu beachten: Mindestens 14 KP der erforderlichen 26 KP aus Kern- und Wahlfächern müssen aus Bereichen der angewandten Mathematik und weiteren anwendungsorientierten Gebieten stammen.)
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Kernfächer aus Bereichen der angewandten Mathematik ... (vollständiger Titel: Kernfächer aus Bereichen der angewandten Mathematik und weiteren anwendungsorientierten Gebieten)
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