tvopt: A Python Framework for Time-Varying Optimization
Project description
Welcome to tvopt
Docs | Installation | Cite
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
tvopt works on Python 3.7 and depends on: numpy, scipy.
pip installation
pip install tvopt
Cite
@inproceedings{bastianello_tvopt_2021,
title = {tvopt: {A} {Python} {Framework} for {Time}-{Varying} {Optimization}},
doi = {10.1109/CDC45484.2021.9683695},
booktitle = {2021 60th {IEEE} {Conference} on {Decision} and {Control} ({CDC})},
author = {Bastianello, Nicola},
year = {2021},
pages = {227--232},
}
Author
tvopt is developed by Nicola Bastianello
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
tvopt-0.2.6.tar.gz
(48.6 kB
view details)
File details
Details for the file tvopt-0.2.6.tar.gz
.
File metadata
- Download URL: tvopt-0.2.6.tar.gz
- Upload date:
- Size: 48.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 colorama/0.4.4 importlib-metadata/4.6.4 keyring/23.5.0 pkginfo/1.8.2 readme-renderer/34.0 requests-toolbelt/0.9.1 requests/2.25.1 rfc3986/1.5.0 tqdm/4.57.0 urllib3/1.26.5 CPython/3.10.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7b4bb8b6c4d14eb98e204307a7352ed265937f5d76b098dc1e47a2f0eedeae0a |
|
MD5 | 728c2dba195018b1ac3ca2f38dc34e2d |
|
BLAKE2b-256 | 952a67f4eea3727eb57aece8ea4e1152be69b4ea16f5f8978e627c445dd4c88b |