optimization-tutorial
sqpdfo
| optimization-tutorial | sqpdfo | |
|---|---|---|
| 1 | 1 | |
| 17 | 13 | |
| - | - | |
| 0.0 | 0.0 | |
| about 2 years ago | over 1 year ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
optimization-tutorial
-
Gradient-Free-Optimizers A collection of modern optimization methods in Python
I will look into this algorithm. Thanks for the suggestion. I have some basic explanations of the optimization techniques and their parameters in a separate repository: https://github.com/SimonBlanke/optimization-tutorial
But there is still a lot of work to be done.
sqpdfo
-
Gradient-Free-Optimizers A collection of modern optimization methods in Python
If you have an expensive but not high dimensional problem you might want to try https://github.com/DLR-SC/sqpdfo .
What are some alternatives?
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
BayesianOptimization - A Python implementation of global optimization with gaussian processes.
Gradient-Free-Optimizers - Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
surrogate-models - A collection of surrogate models for sequence model based optimization techniques
sigopt-server - Open Source version of SigOpt API, performing hyperparameter optimization and visualization
pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints