227-0707-00L  Optimization Methods for Engineers

SemesterSpring Semester 2021
LecturersJ. Smajic
Periodicityyearly recurring course
Language of instructionEnglish


227-0707-00 GOptimization Methods for Engineers2 hrs
Thu10:15-12:00CHN C 14 »
J. Smajic

Catalogue data

AbstractFirst half of the semester: Introduction to the main methods of numerical optimization with focus on stochastic methods such as genetic algorithms, evolutionary strategies, etc.
Second half of the semester: Each participant implements a selected optimizer and applies it on a problem of practical interest.
ObjectiveNumerical optimization is of increasing importance for the development of devices and for the design of numerical methods. The students shall learn to select, improve, and combine appropriate procedures for efficiently solving practical problems.
ContentTypical optimization problems and their difficulties are outlined. Well-known deterministic search strategies, combinatorial minimization, and evolutionary algorithms are presented and compared. In engineering, optimization problems are often very complex. Therefore, new techniques based on the generalization and combination of known methods are discussed. To illustrate the procedure, various problems of practical interest are presented and solved with different optimization codes.
Lecture notesPDF of a short skript (39 pages) plus the view graphs are provided
Prerequisites / NoticeLecture only in the first half of the semester, exercises in form of small projects in the second half, presentation of the results in the last week of the semester.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersJ. Smajic
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationoral 30 minutes
Additional information on mode of examinationDie Prüfung kann auch auf Deutsch abgelegt werden.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

No public learning materials available.
Only public learning materials are listed.


No information on groups available.


There are no additional restrictions for the registration.

Offered in

Electrical Engineering and Information Technology MasterRecommended SubjectsWInformation
Electrical Engineering and Information Technology MasterSpecialization CoursesWInformation
Electrical Engineering and Information Technology MasterSpecialization CoursesWInformation
Electrical Engineering and Information Technology MasterRecommended SubjectsWInformation
Computer Science BachelorMinor CoursesWInformation
Computational Science and Engineering BachelorElectromagneticsWInformation
Computational Science and Engineering MasterElectromagneticsWInformation