Introduction to Optimization Systems (formerly "Entscheidungsunterstützungssysteme")
Exam number: 6052 (6040)
Semester: from 4th semester (Schwerpunktausbildung)
Duration of the module: One semester
Form of the module (i.e. obligatory, elective etc.): Elective
Frequency of module offer: Each summer semester
Prerequisites: Comlpeted basic studies (until and including the 3rd semester), good knowledge and serious interest in quantitative methods
Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.
Person responsible for module: Prof. Dr. Achim Koberstein
Name of the professor: Prof. Dr. Achim Koberstein
Language of teaching: English (formerly conducted in German language under the title "Entscheidungsunterstützungssysteme")
ECTS-Credits (based on the workload): 6
Workload and its composition (self-study, contact time):
Contact time (lecture, tutorials, seminar etc.) 45 h; self-study: 135 h
Contact hours (per week in semester): 4
Methods and duration of examination:
Successful written exam (120 min)
Emphasis of the grade for the final grade: Please check regulations of the study programme
Aim of the module (expected learning outcomes and competencies to be acquired):
The participants learn to model and analyze complex decision situations in business organizations. They acquire the capability to apply special modelling techniques and select appropriate solution methods to solve the models and investigate the generated solutions. Furthermore, they will get to know basic architectures of model based optimization system and state-of-the-art modelling and solver software building the core parts of such systems.
Contents of the module:
Based on quantitative models from the field of applied mathematical optimization this module conveys the core technologies in the field of model based optimization systems and prescriptive analytics.
1. Introduction to Optimization Systems
2. Linear Models and Optimization
3. Solution Software and Modeling Languages
4. Mixed-integer Linear Models and Optmization
5. Solution Methods for LPs and MIPs
6. Special MIP-Models
7. Optimization under Uncertainty
Teaching and learning methods:
Lectures are accompanied by tutorials and homework assignment. As a student you are expected to solve the exercises given as assignment by yourself, often using a computer. The PC pools are available in the seminar building August-Bebel-Strasse 12. You may also use your own PC if you have one.
Literature (compulsory reading, recommended literature):
Suhl, Mellouli: Optimierungssysteme, Springer 2006. (in German)
Williams: Model Building in Mathematical Programming, John Wiley and Sohns 1999.
Kallrath, Wilson: Business Optimization using Mathematical Programming, Macmillan Press 1997.
Heipke: Applications of optimization with Xpress-MP, Dash Optimization Ltd., 2000.
Registration in Moodle Viadrina required.