(With apologies for cross posting)
Are you interested in understanding how evolutionary algorithms and
other randomized search heuristics work? Consider submitting and
attending the FOGA 2025 conference in Leiden! Yes, FOGA is not just for
theoreticians 😉
18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms
FOGA XVIII, Aug 27 – 29, 2025, Leiden, The Netherlands
https://naco.liacs.nl/foga2025/
+ extra day for COST action ROAR-NET meeting on Aug 26:
https://naco.liacs.nl/foga2025//roarnet.html
:: FOGA submission deadline: May 2, 2025
:: FOGA keynote speakers:
-- Joshua D. Knowles, Schlumberger,
https://www.birmingham.ac.uk/staff/profiles/computer-science/honorary-staff/knowles-joshua
-- Stephanie Wehner, Delft University of Technology, The Netherlands,
https://qutech.nl/person/stephanie-wehner/
-- Tobias Glasmachers, Ruhr-Universität Bochum, Germany,
https://www.ini.rub.de/the_institute/people/tobias-glasmachers/
:: Further information: All relevant information can be found on the
website: https://naco.liacs.nl/foga2025/
:: Note that FOGA is _not_ only focused on mathematical analysis of
randomized search heuristics, but aims at covering the entire spectrum
of work, ranging from rigorously derived mathematical results to
carefully crafted empirical studies, as long the key contribution is in
helping us understand why something is happening.
The FOGA series aims at advancing our understanding of the working
principles behind evolutionary algorithms and related randomized search
heuristics, such as local search algorithms, differential evolution, ant
colony optimization, particle swarm optimization, artificial immune
systems, simulated annealing, and other Monte Carlo methods for search
and optimization. Connections to related areas, such as Bayesian
optimization and direct search, are of interest as well. FOGA is the
premier event to discuss advances on the theoretical foundations of
these algorithms, tools needed to analyze them, and different aspects of
comparing algorithms' performance. 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
- (On- and offline) 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 aspects, including performance measures, the selection of
meaningful benchmark problems, and statistical aspects
- Connection between randomized search and machine learning
Please address all questions concerning the CfP to the program chairs
(Jonathan Fieldsend and Francisco Chicano) and all other questions to
the general and local organization team (Thomas Bäck, Anna V. Kononova,
and Elena Raponi)
Looking forward to seeing you in Leiden,
FOGA organizers
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