l2rpn-baselines
L2RPN Baselines a repository to host baselines for l2rpn competitions. (by rte-france)
osqp_benchmarks
QP Benchmarks for the OSQP Solver against GUROBI, MOSEK, ECOS and qpOASES (by osqp)
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| l2rpn-baselines | osqp_benchmarks | |
|---|---|---|
| 1 | 2 | |
| 74 | 90 | |
| - | - | |
| 5.2 | 0.0 | |
| 7 days ago | 11 months ago | |
| Python | Python | |
| Mozilla Public License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
l2rpn-baselines
Posts with mentions or reviews of l2rpn-baselines.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-30.
osqp_benchmarks
Posts with mentions or reviews of osqp_benchmarks.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-30.
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Optimization solvers: missing link for fully open-source energy system modeling
OSQP is fast, but only for QP, not LP. The "benchmarks" (https://github.com/osqp/osqp_benchmarks) include some important problem classes but are random so, for general QP, are not valid. On the industry standard benchmarks (http://plato.asu.edu/ftp/qpbench.html) OSQP doesn't look so good, and it's not even tested against commercial solvers (http://plato.asu.edu/ftp/cconvex.html). Our experience with it on general benchmarking problems is that it can struggle to get sufficiently accurate dual values to the extent that it fails to solve them. For certain classes of important QP problems, and when optimization to small tolerances is not required, it's undoubtedly a great solver - but it's not a general solver.
What are some alternatives?
When comparing l2rpn-baselines and osqp_benchmarks you can also consider the following projects:
fast-reid - SOTA Re-identification Methods and Toolbox
osqp-eigen - Simple Eigen-C++ wrapper for OSQP library
PPO-PyTorch - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
freqtrade-gym - A customized gym environment for developing and comparing reinforcement learning algorithms in crypto trading.