We invite you to submit your high-quality articles to the seventeenth
conference on the foundations of genetic algorithms (FOGA). 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.
== Scope ==
Topics of interest, both of theoretical and empirical nature, 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 black-box optimization and machine learning
== Important Dates ==
– Submissions due: April 27, AoE
– Acceptance notification: June 23
– Camera-ready versions due: July 6
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