FOGA (Foundations of Genetic Algorithms) is a biannual workshop (except for the 3-year gap between FOGA 2002 and FOGA 2005) that started in 1990 in Bloomington, Indiana, USA. Initially dedicated to the theory of Genetic Algorithms (as its name indicates), FOGA rapidly evolved to cover the whole field of Evolutionary Computation. However, the FOGA brand was already well-known and has hence been preserved.
Today, the FOGA workshop 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 in the theoretical foundations of these algorithms, tools needed to analyze them, and different aspects of comparing algorithm performance. Topics of interest include, but are not limited to:
Submissions covering the entire spectrum of work, ranging from rigorously derived mathematical results to carefully crafted empirical studies, are invited.
FOGA is a single track workshop. Its proceedings are published by the ACM.
The 2023 edition of FOGA will be held in Potsdam, Germany, from August 30 to September 1.
Today, the FOGA workshop 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 in the theoretical foundations of these algorithms, tools needed to analyze them, and different aspects of comparing algorithm 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
- Connections between black-box optimization and machine learning
Submissions covering the entire spectrum of work, ranging from rigorously derived mathematical results to carefully crafted empirical studies, are invited.
FOGA is a single track workshop. Its proceedings are published by the ACM.
The 2023 edition of FOGA will be held in Potsdam, Germany, from August 30 to September 1.
The complete history as well as all references to FOGA papers can be found on the corresponding DBLP page