Code for Revisiting a Cutting Plane Method for Perfect Matchings

This is an example implementation, in Python 3, of the minimum-cost perfect matching algorithm described in Chen, Cheung, Kielstra, and Winn's paper Revisiting a Cutting Plane Method for Perfect Matchings.  It currently uses SciPy to solve linear programs, but will work with any black-box LP solver with only minor alterations.

This is academic example code, not suitable for use in a production environment.

Requirements

• SciPy
• NumPy
• igraph

Usage

import cpmatching
import cpmatching.io as io
from igraph import Graph

G = Graph()
G.add_vertices(16)
G.add_edges([[13, 15], [11, 14], [10, 11], [10, 14], [9, 11], [8, 11], \
[7, 12], [5, 15], [5, 13], [4, 11], [4, 13], [3, 7], [2, 6], [2, 13], \
[1, 5], [0, 1], [0, 3], [0, 12], [8, 9], [4, 12]])
G.es["weight"] = 1

x = cpmatching.find_matching(G)

io.pretty_print_solution(G, x)

Further details are available in README.md.