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

Totally Unimodular Node–Arc Incidence Matrices: Medium Collection A (1000 - 20,000 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 1000 and 20 000. 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 benchmarking medium-sized network flow and minimum-cost flow solvers, and studying algorithmic scalability.

Files

README.md

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