ECF is a C++ framework intended for application of any type of
evolutionary
computation. Current features include:
- parameterless: genotype (individual structure) is the only
mandatory parameter
- algorithms: steady state tournament, generational roulette-wheel,
elimination, particle swarm optimization (PSO),
differential evolution (DE),
genetic annealing, artificial bee colony (ABC),
clonal selection (CLONALG),
immune optimization (optIA),
evolution strategy, random search
- genetic
algorithm genotypes
(bitstring, binary encoded real values, floating point vectors, permutation vectors),
genetic
programming genotype (tree), analytic programming
- individuals may contain any genotypes in any number
- many examples: GP symbolic regression,
GP artificial ant,
function
optimization,
TSP,
onemax, function optimization from CEC Real-Parameter Numerical Optimization
- configurable environment: changing algorithm, genotypes and parameters
without recompilation
- checkpointing
and population restoring, various termination criteria,
repeated runs,
crx and mutation operators selection and usage rate, migration
Download
Documentation
These files are also included in the package (./help directory).
Integration with COCO benchmark:

Support:
References
Contributors
(Alphabetical order): Hrvoje Ban, Vinko Bedek, Igor Bespaljko, Iva Brajer, Luka Donđivić,
Luka Franov, Zvonimir Fras,
Danko Komlen, Ivan Kokan, Luka Krizan, Maja Legac, Tomislav Novak,
Lovro Paić-Antunović, Stjepan Picek, Dražen Popović, Ángel Ferreira-Santiago, Domagoj
Stanković, Ivana Stokić, Mirjam Škarica
Project leader & support contact: Domagoj Jakobović (domagoj.jakobovic @
fer.hr)
Acknowledgements
ECF software uses the following components:
Additionally, this project was inspired by
OpenBEAGLE, a comprehensive OO
evolutionary framework.