hwiberg/OptiCL

An end-to-end framework for mixed-integer optimization with data-driven learned constraints.

/ 100

Established

140 stars and 11 monthly downloads. No commits in the last 6 months. Available on PyPI.

Stale 6m

Maintenance 0 / 25

Adoption 12 / 25

Maturity 25 / 25

Community 17 / 25

Stars

140

Forks

Language

Jupyter Notebook

License

MIT

Category

Last pushed

Sep 04, 2023

Monthly downloads

Commits (30d)

Dependencies

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/hwiberg/OptiCL"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Related frameworks

SimonBlanke/Gradient-Free-Optimizers

Lightweight optimization with local, global, population-based and sequential techniques across...

emdgroup/baybe

Bayesian Optimization and Design of Experiments

Gurobi/gurobi-machinelearning

Formulate trained predictors in Gurobi models

heal-research/pyoperon

Python bindings and scikit-learn interface for the Operon library for symbolic regression.

simon-hirsch/ondil

A package for online distributional learning.