CONVERGENCE PROOF FOR THE GENCOL ALGORITHM IN THE CASE OF TWO-MARGINAL OPTIMAL TRANSPORT

Gero Friesecke, Maximilian Penka

Research output: Contribution to journalArticlepeer-review

Abstract

The recently introduced Genetic Column Generation (GenCol) algorithm has been numerically observed to efficiently and accurately compute high-dimensional optimal transport (OT) plans for general multi-marginal problems, but theoretical results on the algorithm have hitherto been lacking. The algorithm solves the OT linear program on a dynamically updated low-dimensional submanifold consisting of sparse plans. The submanifold dimension exceeds the sparse support of optimal plans only by a fixed factor β. Here we prove that for β ≥ 2 and in the two-marginal case, GenCol always converges to an exact solution, for arbitrary costs and marginals. The proof relies on the concept of c-cyclical monotonicity. As an offshoot, GenCol rigorously reduces the data complexity of numerically solving two-marginal OT problems from O(ℓ2) to O(ℓ) without any loss in accuracy, where ℓ is the number of discretization points for a single marginal. At the end of the paper we also present some insights into the convergence behavior in the multi-marginal case.

Original languageEnglish
Pages (from-to)263-275
Number of pages13
JournalMathematics of Computation
Volume94
Issue number351
DOIs
StatePublished - Jan 2025

Keywords

  • column generation
  • convergence
  • genetic algorithm
  • Optimal transport

Fingerprint

Dive into the research topics of 'CONVERGENCE PROOF FOR THE GENCOL ALGORITHM IN THE CASE OF TWO-MARGINAL OPTIMAL TRANSPORT'. Together they form a unique fingerprint.

Cite this