ANL-CEEESA/MIPLearn
1
0
Fork 0
mirror of https://github.com/ANL-CEEESA/MIPLearn.git synced 2025-12-06 01:18:52 -06:00
Code Issues Packages Projects Releases Wiki Activity

README.md: Minor changes

Browse Source
This commit is contained in:
Alinson S. Xavier
2020-01-29 09:58:12 -06:00
parent cdfb1ad053
commit f71c9a969d
1 changed files with 1 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@@ -202,7 +202,7 @@ benchmark.parallel_solve(test_instances)
MIPLearn provides a selection of random instance generators for some fundamental discrete optimization problems, as well a baseline MIP and ML formulation for these problems. The included problems are the following: MIPLearn provides a selection of random instance generators for some fundamental discrete optimization problems, as well a baseline MIP and ML formulation for these problems. The included problems are the following:
* **Maximum Weight Stable Set Problem:** Given a graph G=(V,E) with vertex weights, the problem is to find the maximum weight *stable set* of the graph, where a *stable set* a set of vertices, no two of which are adjacent. The class `MaxWeightStableSetGenerator` can generate random instances of this problem with specified probability distributions for number of vertices, edge probability and weights. * **Maximum Weight Stable Set Problem:** Given a graph G=(V,E) with vertex weights, the problem is to find a maximum weight stable set of the graph, where a *stable set* is a subset of vertices, no two of which are adjacent. The class `MaxWeightStableSetGenerator` can generate random instances of this problem with specified probability distributions for number of vertices, edge probability and weights.
### Benchmark results ### Benchmark results