Python MIP (Mixed-Integer Linear Programming) Tools

Package website: http://python-mip.com

Python MIP is a collection of Python tools for the modeling and solution
of Mixed-Integer Linear programs (MIPs). MIP syntax was inspired by
Pulp. Just like
CyLP it also provides access to
advanced solver features like cut generation, lazy constraints, MIPstarts
and solution Pools. Porting Pulp and Gurobi models should be quite easy.

Some of the main features of MIP are:

high level modeling: write your MIP models in Python as easily as in
high level languages such as
MathProg:
operator overloading makes it easy to write linear expressions in Python;
full featured:
- cut generators and lazy constraints: work with strong formulations with a
  large number of constraints by generating only the required inequalities
  during the branch and cut search;
- solution pool: query the elite set of solutions found during the search;
- MIPStart: use a problem dependent heuristic to generate initial feasible
  solutions for the MIP search.
fast: the Python MIP package calls directly the native dynamic loadable
library of the installed solver using the modern python
CFFI module; models
are efficiently stored and optimized by the solver and MIP transparently
handles all communication with your Python code; it is also compatible
with the Pypy just in time compiler, meaning that
you can have a much better performance, up to 25 times faster for the
creation of large MIPs, than the official Gurobi python interface
which only runs on CPython;
multi solver: Python MIP was written to be deeply integrated with the
C libraries of the open-source COIN-OR Branch-&-Cut
CBC solver and the commercial solver
Gurobi; all details of communicating with
different solvers are handled by Python-MIP and you write only one
solver independent code;
written in modern typed Python 3 (requires Python 3.6 or newer).

Examples

Many Python-MIP examples are documented at https://docs.python-mip.com/en/latest/examples.html

The code of these examples and additional ones (published in tutorials) can be downloaded at https://github.com/coin-or/python-mip/tree/master/examples

Documentation

The full Python-MIP documentation is available at
https://docs.python-mip.com/en/latest/

A PDF version is also available:
https://python-mip.readthedocs.io/_/downloads/en/latest/pdf/

Mailing list

Questions, suggestions and feature request can be posted at Discussions.

Build status

Dependency	Optional
cffi	false
gurobipy	true
matplotlib	true
networkx	true
numpy	true
pytest	true

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mip

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