PySCIPOpt
pyomo
| PySCIPOpt | pyomo | |
|---|---|---|
| 5 | 14 | |
| 749 | 1,844 | |
| 1.3% | 1.5% | |
| 9.4 | 10.0 | |
| 5 days ago | 5 days ago | |
| JetBrains MPS | Python | |
| MIT License | GNU General Public License v3.0 or later |
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.
PySCIPOpt
- GitHub - scipopt/PySCIPOpt: Python interface for the SCIP Optimization Suite
- Python Interface for the SCIP Optimization Suite
-
Rust or C/C++ to learn as a secondary language?
It’s impossible to recommend the right tool for the job, and honestly, depending on how much maths you know it might be hard to make progress, but I’d put money on a constraint solver reducing the time from hours to seconds. Can recommend this one https://github.com/scipopt/PySCIPOpt
-
Python open-source solvers
I guess that pySCIP might be what you are looking for. Note that SCIP only supports linear objectives. However, since quadratic constraints are supported, you can easily use an auxiliary constraint to present the objective, e.g. min z s.t. z <= x*x.
-
Error installing pyscipopt
From the docs (https://github.com/scipopt/PySCIPOpt/blob/master/INSTALL.md#installation-from-pypi)
pyomo
-
pyomo VS timefold-solver - a user suggested alternative
2 projects | 4 Jan 2024
-
[P] Advice needed for what tool/algorithm is appropriate
Pyomo: We tried pyomo still using the same matrix representation as above (5-minutes timeslot interval), but still encountered the same difficulty of expressing program durations as constraint. I seem to not able to make a condition inside the constraint declaration such that if this matrix entry is 1, then do this operation.
-
pyomo VS casadi - a user suggested alternative
2 projects | 5 Sep 2023
-
Elevate Your Python Skills: Machine Learning Packages That Transformed My Journey as ML Engineer
Alternative: pyomo
-
Are there any mathematical optimizations modeling libraries made for Common Lisp?
I’m looking for something similar to Pyomo for Python. Something that connects on the backend to something like GLPK, CBC, IPOPT. Using Google, I’ve only been able to find a few linear programming libraries. If anyone could point me the right direction, it would be greatly appreciated!
- What software is used in the field these days?
-
Operations research packages
Pyomo, it even has its own book. Additionally, CVXOPT focuses on convex optimization, PuLP on linear programming (it has lots of interfaces for other solvers).
-
flopt: powerful optimization modeling tool
There are some optimization modeling tools, Pulp andScipy are known for linear programming (LP) modeling, CVXOPT and Pyomo for quadratic programming (QP).
-
[Request] As a little side project, I want to map out the most efficient path to take when mowing my lawn. How might I go about doing this?
To rephrase this in math terms, you're looking for the least expensive possible path that covers every node in your yard. As for tools, if you don't mind programming in python, maybe try this: http://www.pyomo.org/.
-
Integer vs. Linear Programming in Python
For modelling libraries in general-purpose languages, Gurobi's python bindings have the best reputation. But of course Gurobi is very expensive (I have heard about $50k for a fully unrestricted license, plus $10k yearly for support). On the open-source side, besides Google's OR-Tools, there is Pyomo [1] and PuLP [2] in Python (as the article mentions). In Julia, there is JuMP [3], whose development community is extremely enthusiastic.
Traditionally, however, mathematical models were encoded in domain-specific languages. The most prominent one is AMPL [4] which is proprietary. The glpk [5] people have developed a very neat open source clone of AMPL: the GNU MathProg language. For a more modern take on AMPL-type modelling DSLs, look at ZIMPL [6], which is open source as well.
[1] http://www.pyomo.org/
[2] https://coin-or.github.io/pulp/
[3] https://jump.dev/JuMP.jl/stable/
[4] https://ampl.com
[5] https://www.gnu.org/software/glpk/
[6] https://zimpl.zib.de/
What are some alternatives?
pulp - A python Linear Programming API
rust-ndarray - ndarray: an N-dimensional array with array views, multidimensional slicing, and efficient operations
or-tools - Google's Operations Research tools:
Bonmin - Basic Open-source Nonlinear Mixed INteger programming
gopy - gopy generates a CPython extension module from a go package.
do-mpc - Model predictive control python toolbox
pyimgui - Cython-based Python bindings for dear imgui
acados - Fast and embedded solvers for nonlinear optimal control
mypyc - Compile type annotated Python to fast C extensions
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.