The FOGA conference series aims at advancing the understanding of the working principles behind Evolutionary Algorithms and related Randomized Search heuristics. It is a premier event to discuss advances in the theoretical foundations of these algorithms, corresponding tools and frameworks suitable 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
• 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

FOGA 2021 invites submissions covering the entire spectrum of work, ranging from rigorously derived mathematical results to carefully designed empirical studies.

All submissions will be subject to a thorough double-blind review with subsequent rebuttal phase. Accepted papers will be included in the FOGA proceedings published by ACM Press.

The list of accepted paper is now available!