Integrality-Gap Bounds for Weighted Matchoids and Matroid Intersection

Yu Cong, Yajie Zhao

For weighted k-matroid intersection with k≥2, the natural LP has integrality gap at most k−1+1/k. A deterministic LP-relative algorithm achieves that factor; the paper separately extends the bound to p-matchoids.

Sources for this record

What was already known

The weighted k=3 gap was already exactly two; for general k≥4 the previous upper bound was k. The conjectured k−1 factor remains open.

AI involvement AI-centered

Cong and Zhao say GPT-5.6 Sol materially assisted the central gap proof and local-ratio algorithm. They formulated and explained the polyhedral argument and verified the manuscript.

The authors report material model assistance in the central gap proof and local-ratio derivation, but do not claim model leadership or autonomy.

Importance Notable

Improves the general weighted LP gap below k for k≥4 and gives a matching algorithmic guarantee.

Limitations

The authors report checking all content, but do not assign specific proof steps to GPT-5.6 Sol. The p-matchoid extension and tight examples retain separate human author credit.

Technical verification Formal (human)

The named authors explicitly report verifying correctness of all content. This is a source-reported completed human check of the assessed theorem and algorithm; no machine check is documented.

Formal checking

Author verification of correctness and originality of all manuscript content

Checker
Yu Cong and Yajie Zhao, paper authors
Scope
Theorem 1.1 weighted k-matroid intersection gap k-1+1/k and the associated LP-relative algorithm
Basis
Reported by the linked checker
Evidence source

Checking a formal statement does not establish that it matches the original problem.

Human understanding Full

The authors explain the closure inequality, aggregation with fractional marginals, and local-ratio construction in §§3–4.

Correction and publication history

2026-10-18 · publication

Improves the general weighted LP gap below k for k≥4 and gives a matching algorithmic guarantee.

Read this published revision