sqpdfo
optimization-tutorial
sqpdfo | optimization-tutorial | |
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1 | 1 | |
13 | 17 | |
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0.0 | 0.0 | |
over 1 year ago | about 2 years ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
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sqpdfo
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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 .
optimization-tutorial
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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.
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.
Gradient-Free-Optimizers - Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
BayesianOptimization - A Python implementation of global optimization with gaussian processes.
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