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SimonBlanke / Gradient-Free-Optimizers

Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
https://simonblanke.github.io/gradient-free-optimizers-documentation
MIT License
1.13k stars 79 forks source link

Implement genetic algorithm #46

Open igaloly opened 2 months ago

igaloly commented 2 months ago

What do you think about implementing more EA algorithms from DEAP

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SimonBlanke commented 2 months ago

Hello @igaloly,

thank you for the suggestion.

I looked into the package you posted. It turns out, that DEAP is the basis for Tpot, which inspired me to create my own package for optimization.

Some of the algorithms in the DEAP package are not fit to be implemented in GFO (because they require a continuous search-space). But I will look into more of the algorithms within the next weeks. If you have a suggestion for a particular algorithm you can post it here and explain it and why it fits GFO.

SimonBlanke commented 1 month ago

After doing some research I further understood the difference between evolution strategies and genetic algorithms. I would like to add a genetic-algorithm-optimizer to GFO and updated to title of this issue accordingly.