gugarosa/opytimizer
🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
Implements a modular architecture where optimization algorithms inherit from base classes, enabling composition of custom meta-heuristics through space definitions, function evaluations, and operator configurations. Provides native support for multi-objective optimization and integrates seamlessly with NumPy for efficient numerical computation on high-dimensional search spaces.
632 stars.
Stars
632
Forks
42
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 16, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/gugarosa/opytimizer"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
jolars/sortedl1
Python package for Sorted L-One Penalized Estimation (SLOPE)
hiroyuki-kasai/SGDLibrary
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
SENATOROVAI/L-BFGS-B-solver-course
Linear regression with the LBFGSB (Limited-memory Broyden-Fletcher-Goldfarb-Shanno BFGS) solver...
loeweX/Forward-Forward
Reimplementation of Geoffrey Hinton's Forward-Forward Algorithm
princeton-vl/CoqGym
A Learning Environment for Theorem Proving with the Coq proof assistant