Online Matching with General Arrivals
Not on the map. Why?
Abstract (arXiv)
The online matching problem was introduced by Karp, Vazirani and Vazirani nearly three decades ago. In that seminal work, they studied this problem in bipartite graphs with vertices arriving only on one side, and presented optimal deterministic and randomized algorithms for this setting. In comparison, more general arrival models, such as edge arrivals and general vertex arrivals, have proven more challenging and positive results are known only for various relaxations of the problem. In particular, even the basic question of whether randomization allows one to beat the trivially-optimal deterministic competitive ratio of frac12 for either of these models was open. In this paper, we resolve this question for both these natural arrival models, and show the following. 1. For edge arrivals, randomization does not help --- no randomized algorithm is better than frac12 competitive. 2. For general vertex arrivals, randomization helps --- there exists a randomized (frac12+Omega(1))-competitive online matching algorithm.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Apr 2019.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 1; 2026: 1.
3 papers.
- 2022Sublinear Time Algorithm for Online Weighted Bipartite Matchingcited by 7
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- 2026Stochastic Matching via Local Sparsification13 May 2026
- 2025Stochastic Matching Bandits with Rare Optimization Updates4 Sep 2025
- 2022Sublinear Time Algorithm for Online Weighted Bipartite Matching5 Aug 2022