English

The Multiple-Choice Matroid Secretary Problem

Data Structures and Algorithms 2026-07-16 v1

Abstract

We introduce and study the multiple-choice matroid secretary problem, denoted (J,κ)(J,\kappa)-MSP. For rank-one matroids and κ=\kappa=\infty, it reduces to the classical secretary problem with JJ choices. Elements arrive in uniformly random order. Algorithms may keep a candidate pool AUX\mathrm{AUX} feasible in the JJ-fold union matroid M(J)\mathcal{M}^{(J)} satisfying AUXκrank(M)|\mathrm{AUX}|\le \kappa\cdot\mathrm{rank}(\mathcal{M}). Finally, one extracts the maximum-weight independent subset of AUX\mathrm{AUX} in M\mathcal{M}. This model separates online storage from the final feasible solution. We study two multiple-choice implementations: multi-track algorithms (maintaining JJ independent sets of M\mathcal{M}) and union-based algorithms (maintaining the pool directly in M(J)\mathcal{M}^{(J)}). Our main result is an exact optimal algorithm for transversal matroids in the uncapacitated (J,)(J,\infty) setting. For fixed JJ, its probability-competitive ratio equals the optimal success probability of the classical JJ-choice secretary problem. Thus, rank-one instances are the worst case for the whole transversal class, and the optimal guarantee converges exponentially fast to 11 as JJ grows. We also analyze a simple single-threshold routing algorithm for capacitated transversal matroids with local capacities bb and global capacity κrank(M)\kappa\cdot\mathrm{rank}(\mathcal{M}). Its analysis provides explicit finite-parameter bounds and asymptotic formulas, showing how finite-rank loss caused by global capacity decays, and how bb, JJ, and κ\kappa interact. Finally, we instantiate the multi-track approach for kk-column-sparse matroids (guarantee 1O(eJ/(ke))1-O(e^{-J/(ke)})) and the union-based approach for laminar matroids (guarantee 1O(eJ/e)1-O(e^{-J/e})).

Cite

@article{arxiv.2607.15407,
  title  = {The Multiple-Choice Matroid Secretary Problem},
  author = {Matías Ortiz-Angel and José A. Soto},
  journal= {arXiv preprint arXiv:2607.15407},
  year   = {2026}
}