godatadriven/evol

a python grammar for evolutionary algorithms and heuristics

46
/ 100
Emerging

This project helps operations researchers and data scientists design and test custom optimization strategies for complex problems. You provide a set of potential solutions and a way to evaluate them, and it outputs improved solutions refined through simulated evolution. It's ideal for practitioners who need fine-grained control over how their solutions evolve and adapt.

193 stars. No commits in the last 6 months. Available on PyPI.

Use this if you need to build and combine specific, step-by-step evolutionary algorithms to find optimal solutions for problems like pathfinding or resource allocation.

Not ideal if you need a black-box hyperparameter optimization tool for machine learning models, or if execution speed is your absolute highest priority.

optimization operations-research algorithm-design simulation complex-systems
Stale 6m
Maintenance 0 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 11 / 25

How are scores calculated?

Stars

193

Forks

12

Language

Python

License

MIT

Last pushed

Apr 07, 2022

Commits (30d)

0

Dependencies

1

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