Published September 27, 2025 | Version v1.0.0
Dataset Open

Totally Unimodular Node–Arc Incidence Matrices: Small Collection (50 - 1000 nodes)

  • 1. EDMO icon Royal Holloway, University of London

Description

 

This dataset contains a collection of totally unimodular (TU) node–arc incidence matrices, generated from random directed graphs with node counts between 50 and 1000. Each column of the incidence matrix has exactly one +1 (arc tail) and one –1 (arc head). Because of the TU property, all linear programming relaxations of integer flow problems are guaranteed to have integer solutions.

The dataset includes:

  • matrices.csv: sparse representation of all instances (two rows per arc, +1 and –1).
  • metadata.csv: summary of each instance (nodes, arcs, density).
  • Conversion scripts (make_dat_all.py, make_dat_all.R) to produce .dat files for AMPL or other solvers.

Typical applications include teaching (small cases), benchmarking network flow and minimum-cost flow solvers, and studying algorithmic scalability.

Files

README.md

Files (634.8 MB)

Name Size Download all
md5:711fb2f67fc3d57522e740ecba7bbb97
3.7 kB Download
md5:1bf12712fda3d9a2a7bc382374e349b3
2.4 kB Download
md5:283ff6c58b3d46b0bbd6477ad46a6c04
634.7 MB Preview Download
md5:5430412696f3b73df27683919233c174
33.9 kB Preview Download
md5:8b1ff39d933f5c85a2aaf34c4c812fa5
2.2 kB Preview Download