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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.
optopy works on Python 3.7 and depends on: numpy, scipy.
pip install optopy
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}
}
optopy is developed by Nicola Bastianello