python-mip
HiGHS
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| python-mip | HiGHS | |
|---|---|---|
| 1 | 3 | |
| 502 | 795 | |
| 2.0% | 5.7% | |
| 7.1 | 9.9 | |
| about 1 month ago | 2 days ago | |
| Python | C++ | |
| Eclipse Public License 2.0 | MIT License |
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.
python-mip
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Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
I've been using CBC via python-mip (https://github.com/coin-or/python-mip). It's great because it's got a super clean interface (milp variables/expressions/constraints), the code is quite accessible, and it's low overhead which makes it good for solving many very small problems.
Community sentiment seems to be beginning to shift toward favouring the HiGHS solver (https://github.com/ERGO-Code/HiGHS) over CBC. Something I'm keeping a close eye on.
nextmv seems to pitch itself as a generic solving ("decision automation") platform or something (unclear). But it seems that the only fleshed out product offering is for vehicle routing, based on the docs. Are there plans to offer, for instance, a solver binary that can be used to solve generic problems?
Also all the github repos under https://github.com/nextmv-io are private, so links from docs are 404.
HiGHS
- Algorithms - Researchers Approach New Speed Limit for Seminal Problem
- HiGHS: High performance open source MILP and QP solver
-
Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
I've been using CBC via python-mip (https://github.com/coin-or/python-mip). It's great because it's got a super clean interface (milp variables/expressions/constraints), the code is quite accessible, and it's low overhead which makes it good for solving many very small problems.
Community sentiment seems to be beginning to shift toward favouring the HiGHS solver (https://github.com/ERGO-Code/HiGHS) over CBC. Something I'm keeping a close eye on.
nextmv seems to pitch itself as a generic solving ("decision automation") platform or something (unclear). But it seems that the only fleshed out product offering is for vehicle routing, based on the docs. Are there plans to offer, for instance, a solver binary that can be used to solve generic problems?
Also all the github repos under https://github.com/nextmv-io are private, so links from docs are 404.
What are some alternatives?
or-tools - Google's Operations Research tools:
SciPy - SciPy library main repository
OptaPlanner - Java Constraint Solver to solve vehicle routing, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.
EA-FC-24-Automated-SBC-Solving - EA FC 24 Automated SBC Solving using Integer Programming ⚽
osqp - The Operator Splitting QP Solver
minizinc-python - Access to all MiniZinc functionality directly from Python
csips - A pure-python integer programming solver
clpz - Constraint Logic Programming over Integers
exact