Onderwijs Informatica en Informatiekunde
Evolutionary computing
| Website: | website containing additional information | ||||||||||||||
| Course code: | INFOEA | ||||||||||||||
| Credits: | 7.5 ECTS | ||||||||||||||
| Period: | period 3 (week 6 through 15, i.e., 8-2-2021 through 16-4-2021; retake week 27) |  | |||||||||||||
| Timeslot: | C | ||||||||||||||
| Participants: | up till now 0 subscriptions | ||||||||||||||
| Schedule: | Official schedule representation can be found in MyTimetable | ||||||||||||||
| Teachers: |
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| Note: | No up-to-date course description available. Text below is from year 2019/2020 | ||||||||||||||
| Contents: | Evolutionary algorithms (EAs) are population-based, stochastic search algorithms based on the mechanisms of natural evolution. We will study how to design representations and variation operators for specific problems. We also analyse convergence behavior and population sizing. We will discuss how to combine EAs with local search heuristics to solve combinatorial optimization problems like graph bipartitioning, graph coloring, bin packing, … . | ||||||||||||||
| Literature: | May change! Lecture slides + papers | ||||||||||||||
| Course form: | Lectures + practical assignment + seminar | ||||||||||||||
| Exam form: | Written exam (= 60% of final grade) + report of the practical assignment (= 30% of final grade) + seminar presentation (= 10% of final grade). | ||||||||||||||
| Minimum effort to qualify for 2nd chance exam: | To qualify for the retake exam, the grade of the original must be at least 4. | ||||||||||||||