Difference between revisions of "FOGA 2021"
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{{Event | {{Event | ||
| − | |Acronym=FOGA | + | |Acronym=FOGA 2021 |
| + | |Title=16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms | ||
| + | |Ordinal=16 | ||
|Series=FOGA | |Series=FOGA | ||
| − | | | + | |Type=Conference |
| − | | | + | |Start date=2021/09/06 |
| − | + | |End date=2021/09/08 | |
| − | + | |Homepage=https://www.fhv.at/foga2021 | |
| − | | | + | |City=Dornbirn |
| − | |Homepage= | + | |Country=Austria |
| + | |presence=online | ||
| + | |Has host organization=FH Vorarlberg | ||
| + | |pageCreator=Soeren | ||
| + | |pageEditor=Heike.Rohde | ||
| + | |contributionType=1 | ||
}} | }} | ||
| + | Topics of interest include, but are not limited to: | ||
| + | |||
| + | Run time analysis | ||
| + | Mathematical tools suitable for the analysis of search heuristics | ||
| + | Fitness landscapes and problem difficulty | ||
| + | Configuration and selection of algorithms, heuristics, operators, and parameters | ||
| + | Stochastic and dynamic environments, noisy evaluations | ||
| + | Constrained optimization | ||
| + | Problem representation | ||
| + | Complexity theory for search heuristics | ||
| + | Multi-objective optimization | ||
| + | Benchmarking | ||
| + | Connections between black-box optimization and machine learning | ||
Latest revision as of 20:19, 1 April 2022
| FOGA 2021 | |
|---|---|
16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms
| |
| Ordinal | 16 |
| Event in series | FOGA |
| Dates | 2021/09/06 (iCal) - 2021/09/08 |
| Presence | online |
| Homepage: | https://www.fhv.at/foga2021 |
| Location | |
| Location: | Dornbirn, Austria |
| Table of Contents | |
Topics of interest include, but are not limited to:
Run time analysis Mathematical tools suitable for the analysis of search heuristics Fitness landscapes and problem difficulty Configuration and selection of algorithms, heuristics, operators, and parameters Stochastic and dynamic environments, noisy evaluations Constrained optimization Problem representation Complexity theory for search heuristics Multi-objective optimization Benchmarking Connections between black-box optimization and machine learning