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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