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192.137 Heuristic Optimization Techniques
Diese Lehrveranstaltung ist in allen zugeordneten Curricula Teil der STEOP.
Diese Lehrveranstaltung ist in mindestens einem zugeordneten Curriculum Teil der STEOP.

2022W, VU, 3.0h, 4.5EC


  • Semesterwochenstunden: 3.0
  • ECTS: 4.5
  • Typ: VU Vorlesung mit Übung
  • LectureTube Lehrveranstaltung
  • Format der Abhaltung: Hybrid


Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage...

verschiedene heuristische Algorithmen zur Lösung schwieriger Optimierungsprobleme zu verstehen, anzuwenden und für neue Probleme zu adaptieren.

Inhalt der Lehrveranstaltung

This lecture deals with heuristic methods to solve optimization problems. The presented approaches are especially suitable for problems arising in practice. On the one hand such problems are often too complex to be solved in an exact way because of the increasing amount of computation time needed by conventional exact techniques. On the other hand it is often sufficient or even required to come up with a good solution in reasonable time.

In this course we primarily focus on discrete appilcation problems and application in areas such as transport optimization, scheduling, network design, cutting and packing.

The methods considered in the course include:

  • Construction Heuristics
  • Local Search
  • Simulated Annealing
  • Tabu-Search
  • Guided Local Search
  • Variable Neighborhood Search
  • Very Large Neighborhood Search
  • Greedy Randomized Adaptive Search Procedure
  • Genetic Algorithms
  • Evolutionary Strategies
  • Ant Colony Optimization
  • Hybridization of different approaches, parallelization
  • Analysis and Tuning of metaheuristics

Beside the theoretical basics this lecture focuses on practical applications and the connection of metaheuristics with problem-specific heuristics as well as some examples of suitable combinations with exact methods.

Also we will discuss how to properly tune heuristics and to evaluate and compare them by means of experiments and appropriate statistical methods.


Introduction and explanation of general methods, discussion of examples, theoretical exercises, hands-on programming exercises, presentation and discussion of solutions.



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 20.0h Lectures
 50.0h Exercises and recap of the lecture contents
 40.0h Programming exercises
   2.5h Exercise interviews / Examination

Hotline for any questions concerning this course: heuopt (at)

Vortragende Personen


LVA Termine

Di.11:00 - 13:0004.10.2022 - 24.01.2023EI 8 Pötzl HS - QUER Vorlesung
Heuristic Optimization Techniques - Einzeltermine
Di.04.10.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.11.10.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.18.10.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.25.10.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.08.11.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.22.11.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.29.11.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.06.12.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.13.12.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.20.12.202211:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.10.01.202311:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.17.01.202311:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung
Di.24.01.202311:00 - 13:00EI 8 Pötzl HS - QUER Vorlesung


Assignments / Oral Exam / Grading

During the course five assignments are given out:

  • Three pen & paper exercise sheets with theoretical tasks and
  • two programming exercises where you solve an optimization problem by implementing optimization algorithms.

The pen & paper exercises should be solved alone while the programming exercises are meant to be solved in teams of two students. For all five assignments concise reports should be prepared and handed in.

The five assignments are discussed in three online interview sessions:

  • First interview session between 7th and 18th of November 2022: pen & paper sheet 1
  • Second interview session between 05th and 16th of December 2022: pen & paper sheet 2 + programming exercise 1
  • Third interview session between 16th and 27th of January 2023: pen & paper sheet 3 + programming exercise 2

In each of the interview sessions, the assignments are discussed - based on the uploaded reports. Additionally, in the course of the discussion of the pen & paper sheets, questions about the corresponding course topics are asked. Each of the five assignments contributes 20% to the final grade. To pass the cource you need to achieve at least 50% of the points of the 3 pen & paper sheets and at least 50% of the points of the 2 programming exercises.

The registration for the interview sessions is possible on TUWEL where several time slots for each interview session will be offered.


Von Bis Abmeldung bis
12.09.2022 00:00 16.10.2022 23:55 16.10.2022 23:55


066 504 Masterstudium Embedded Systems Keine Angabe
066 645 Data Science Keine Angabe
066 646 Computational Science and Engineering Keine Angabe
066 931 Logic and Computation Gebundenes Wahlfach
066 932 Visual Computing Gebundenes Wahlfach
066 937 Software Engineering & Internet Computing Keine Angabe
066 938 Technische Informatik Gebundenes Wahlfach


  • F. Glover, G. A. Kochenberger: Handbook of Metaheuristics, Kluwer Academic Publishers, 2003
    (comprehensive, recent standard work on metaheuristics)
  • M. Gendreau, J.-Y. Potvin: Handbook of Metaheuristics, 2nd edition, Springer, 2010
    (describes various methods in addition to the first version)
  • E. Talbi: Metaheuristics: From Design to Implementation, J. Wiley and Sons, 2009
    (new and detailed work about metaheuristics)


Basic knowledge in algorithms and data structures, programming skills

Vorausgehende Lehrveranstaltungen

Begleitende Lehrveranstaltungen

Vertiefende Lehrveranstaltungen

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