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License: Other
Framework for solving discrete optimization problems using a combination of Mixed-Integer Linear Programming (MIP) and Machine Learning (ML)
License: Other
Hi iSoron, when I use MIPlearn to solve the Power Grid Lib - Unit Commitment (https://github.com/power-grid-lib/pglib-uc#power-grid-lib---unit-commitment, about 300,000 variables), I find that the set_instance() method in the solve() method runs very slowly (several hours). Is there any other way to make it faster?
I want to save the instances generated by the instance generator, but I can't find the API. I would greatly appreciate it with your generous assistance.
IIRC, only CPLEX could work with infeasible starting point. If feeding infeasible starting point into Gurobi or COPT or other MIP solvers, the starting point would not be respected thus those solvers would still start with their own initial guesses. So my question is, for a large and hard MIP problem (like SCUC), how to make sure or are we sure that the ML learner would always give the feasible solution?
Great work by the way.
On MacOS 10.15.6 with python 3.8.5 installed via brew, changing line 18 in the Makefile to
cd src/python && python3 setup.py install
then make install
is seemingly successful (except the Julia installation error).
However, in python3, I have an error loading miplearn:
Python 3.8.5 (default, Jul 21 2020, 10:48:26)
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import miplearn
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<frozen zipimport>", line 259, in load_module
File "/usr/local/lib/python3.8/site-packages/miplearn-0.1-py3.8.egg/miplearn/__init__.py", line 10, in <module>
ModuleNotFoundError: No module named 'miplearn.components'
The same issue does not happen when using make develop
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