Table of Contents


Below you can see the schedule for winter semester 2022/23. The linked lecture materials come from previous runs of the course, and they can (and probably will) be updated during the actual semester. The order of lectures can change.


  • PP: Petr Pošík

Competencies you should get after each lecture.


The order and contents of the lectures can change, including the competencies!

datum č.t. S/L Lecturer Contents Materials Reading
19.09. 1. S PP Optimization. Local search and evolutionary algorithms. Slides. Handouts. (Updated 20220919.) Chapters 1, 2, intro of 3 and 3.2 from [Luke2009]
PP Lecture in the exercise time slot: Successful applications of EAs. applications_of_eas_2022.pptx (WARNING: BIG FILE), applications_of_eas_2022.pdf
26.09. 2. L PP Discrete EAa. Binary representation, permutations. Slides. Handouts. (Updated 20210929.) MTSP video Chapters 3.2, 3.3, 4.1 from [Luke2009].
03.10. 3. S PP EAs with real representation. Slides. Handouts. (Updated 20221003.) Chapters 3.1, 3.2, 3.4, 4.1, 9.2.3 from [Luke2009].
10.10. 4. L PP EA with real representation (part 2). Other types of metaheuristics: PSO. ACO. Slides. Handouts. (Updated 20221010.) Chapters 3.4, 3.5 and 8 (esp. 8.3) from [Luke2009].
17.10. 5. S PP No Free Lunch. Comparing performance of EAs. Slides. Handouts. (Updated 20221017.) Chapter 11 from [Luke2009], esp. 11.1 - 11.2.
24.10. 6. L PP Multiobjective optimization. Dominance, Pareto optimality. NSGAII, SPEA2. Slides. Handouts. (Updated 20221024.) Examples of real applications Chapter 7 from [Luke2009].
31.10. 7. S PP Constraints. Penalization, stochastic ranking, multiobjective approach. Slides. Handouts. (Updated 20211130.) a0m33eoa_constrainthandling.pdf
07.11. 8. L PP Genetic programming. Basic principles and applications. Slides. Handouts. (Updated 20211108.) Chapters 3.3.3, 4.3 from [Luke2009].
14.11. 9. S PP Grammatical evolution, Cartesian GP. Slides. Handouts. (Updated 20211115.)
21.11. 10. L PP Estimation of Distribution Algorithms. Slides. Handouts. (Updated 20211122.) Chapter 9 from [Luke2009].
28.11. 11. S PP Parallel EAs, coevolution. Slides. Handouts. (Updated 20211129) Chapters 5 and 6 from [Luke2009].
05.12. 12. L PP Parameters of EAs: tuning and adaptation. Slides. Handouts. (Updated 20211206.)
12.12. 13. S Bonus: Quality-Diversity Optimization (no in-person lecture, watch it online) GECCO 2021 QD Tutorial + slides (access from FEL or via FEL VPN). Alternative: ICML 2019 Tutorial
09.01. 14. S PP Presentations of semestral tasks.


Neither lectures nor the labs are streamed/recorded this year. Below you can find recordings of online lectures in BigBlueButton from 2020/21 with Jiří Kubalík and Petr Pošík as the lecturers.

  1. Intro to optimization + Applications of EAs. BBB. (Bad sound in the first part. :-( )
  2. Simple genetic algorithms. BBB.
  3. Evolution Strategies. BBB.
  4. Evolution Strategies + other types of metaheuristics. BBB.
  5. No Free Lunch + Empirical Comparisons of Stochastic Algorithms. BBB.
  6. Multiobjective EAs. BBB.
  7. Constraints. BBB.
  8. Genetic Programming. BBB.
  9. Grammatical Evolution. Cartesian GP. BBB.
  10. Estimation of Distribution Algorithms. BBB.
  11. Parallel Genetic Algorithms. Coevolution. BBB.
  12. GP Issues. Parameter Tuning. BBB.
courses/a0m33eoa/lectures/start.txt · Last modified: 2022/12/05 14:29 by xposik