Welcome to optopy 
Docs | Installation | Cite
At present, optopy is a clone of tvopt, but in the future it will include more functionalities, with the goal of delivering a module suited to the benchmarking of both static and dynamic optimization algorithms.
tvopt is a prototyping and benchmarking Python framework for time-varying (or online) optimization. The framework is modular, and provides different tools for modeling dynamic optimization problems and to solve them with a wide range of well known algorithms.
The documentation is available here.
Installation
optopy works on Python 3.7 and depends on: numpy, scipy.
pip installation
pip install optopy
Cite
See tvopt and relative reference:
@article{bastianello_tvopt_2020,
title = {tvopt: {A} {Python} {Framework} for {Time}-{Varying} {Optimization}},
url = {http://arxiv.org/abs/2011.07119},
journal = {arXiv:2011.07119 [cs, math]},
author = {Bastianello, Nicola},
year = {2020}
}
Author
optopy is developed by Nicola Bastianello
Metadata
Release files for optopy 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| optopy-0.1.0.tar.gz | 33.6 kB | Details |
Release files / optopy-0.1.0.tar.gz
| Download URL | optopy-0.1.0.tar.gz |
|---|---|
| Size | 33.6 kB |
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