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227-0707-00L 3 Credits BSC , MSC D-ITET , D-INFK , D-MATH

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Optimization Methods for Engineers

Lecturers & Examiners: Prof. Dr. Jasmin Smajic

VVZ CR 3.8

Last Updated: 2026-02-05 16:07:19

Abstract

First 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.

Objective

Numerical 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.

Content

Typical 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.

Resources

Lecture Notes

PDF of a short skript (39 pages) plus the view graphs are provided

General Information

Language: English
Levels: BSC , MSC
Frequency: Yearly recurring

Examination

Type: session examination
Mode: oral 30 minutes

Die Prüfung kann auch auf Deutsch abgelegt werden.

Course Components

Type	Title	Time & Place	Hours
lecture with exercise	Optimization Methods for Engineers	Thu 10:15-12:00 (CHN C 14)	2 h weekly

Offered In

Computational Science and Engineering Bachelor
- Fields of Specialization
  - Electromagnetics
Computer Science Bachelor
- Minor Courses
Computational Science and Engineering Master
- Fields of Specialization
  - Electromagnetics (recognition of 227-0662-00L and 227-0662-10L requires the successful completion of both course units)
Electrical Engineering and Information Technology Master
- Master Studies (Programme Regulations 2018)
  - Electronics and Photonics (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Electronics and Photonics", see . The individual study plan is subject to the tutor's approval.)
    - Specialization Courses (These specialization courses are particularly recommended for the area of "Electronics and Photonics", but you are free to choose courses from any other field in agreement with your tutor. A minimum of 40 credits must be obtained from specialization courses during the Master's Programme.)
  - Signal Processing and Machine Learning (The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Signal Processing and Machine Learning ", see . The individual study plan is subject to the tutor's approval.)
    - Specialization Courses (These specialization courses are particularly recommended for the area of "Signal Processing and Machine Learning", but you are free to choose courses from any other field in agreement with your tutor. A minimum of 40 credits must be obtained from specialization courses during the MSc EEIT.)
- Master Studies (Programme Regulations 2008)
  - Major Courses (A total of 42 CP must be achieved form courses during the Master Program. The individual study plan is subject to the tutor's approval.)
    - Electronics and Photonics
      - Recommended Subjects (These courses are recommended, but you are free to choose courses from any other special field. Please consult your tutor.)
    - Signal Processing and Machine Learning
      - Recommended Subjects