Second Price Matching with Complete Allocation and Degree Constraints

Fuente: arXiv
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Main Authors: Pinchasi, Rom, Singer, Neta, Vogl, Lukas, Wei, Jiaye
Format: Preprint
Published: 2025
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author Pinchasi, Rom
Singer, Neta
Vogl, Lukas
Wei, Jiaye
author_facet Pinchasi, Rom
Singer, Neta
Vogl, Lukas
Wei, Jiaye
contents We study the Second Price Matching problem, introduced by Azar, Birnbaum, Karlin, and Nguyen in 2009. In this problem, a bipartite graph (bidders and goods) is given, and the profit of a matching is the number of matches containing a second unmatched bidder. Maximizing profit is known to be APX-hard and the current best approximation guarantee is $1/2$. APX-hardness even holds when all degrees are bounded by a constant. In this paper, we investigate the approximability of the problem under regular degree constraints. Our main result is an improved approximation guarantee of $9/10$ for Second Price Matching in $(3,2)$-regular graphs and an exact polynomial-time algorithm for $(d,2)$-regular graphs if $d\geq 4$. Our algorithm and its analysis are based on structural results in non-bipartite matching, in particular the Tutte-Berge formula coupled with novel combinatorial augmentation methods. We also introduce a variant of Second Price Matching where all goods have to be matched, which models the setting of expiring goods. We prove that this problem is hard to approximate within a factor better than $(1-1/e)$ and show that the problem can be approximated to a tight $(1-1/e)$ factor by maximizing a submodular function subject to a matroid constraint. We then show that our algorithm also solves this problem exactly on regular degree constrained graphs as above.
format Preprint
id arxiv_https___arxiv_org_abs_2505_06005
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Second Price Matching with Complete Allocation and Degree Constraints
Pinchasi, Rom
Singer, Neta
Vogl, Lukas
Wei, Jiaye
Data Structures and Algorithms
Computational Complexity
Discrete Mathematics
We study the Second Price Matching problem, introduced by Azar, Birnbaum, Karlin, and Nguyen in 2009. In this problem, a bipartite graph (bidders and goods) is given, and the profit of a matching is the number of matches containing a second unmatched bidder. Maximizing profit is known to be APX-hard and the current best approximation guarantee is $1/2$. APX-hardness even holds when all degrees are bounded by a constant. In this paper, we investigate the approximability of the problem under regular degree constraints. Our main result is an improved approximation guarantee of $9/10$ for Second Price Matching in $(3,2)$-regular graphs and an exact polynomial-time algorithm for $(d,2)$-regular graphs if $d\geq 4$. Our algorithm and its analysis are based on structural results in non-bipartite matching, in particular the Tutte-Berge formula coupled with novel combinatorial augmentation methods. We also introduce a variant of Second Price Matching where all goods have to be matched, which models the setting of expiring goods. We prove that this problem is hard to approximate within a factor better than $(1-1/e)$ and show that the problem can be approximated to a tight $(1-1/e)$ factor by maximizing a submodular function subject to a matroid constraint. We then show that our algorithm also solves this problem exactly on regular degree constrained graphs as above.
title Second Price Matching with Complete Allocation and Degree Constraints
topic Data Structures and Algorithms
Computational Complexity
Discrete Mathematics
url https://arxiv.org/abs/2505.06005