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Online Preemptive Matching Revisited

Authors Peter Kiss , Mohammad Sharifi

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LIPIcs.ICALP.2026.128.pdf
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Subject Classification

ACM Subject Classification
  • Theory of computation → Online algorithms
  • Theory of computation → Approximation algorithms analysis
  • Theory of computation → Streaming models
Keywords
  • Online Algorithms
  • Preemptive Algorithms
  • Approximate Maximum Matching

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Abstract

We study the online preemptive matching problem, in which the edges of a graph arrive sequentially and the algorithm must maintain a matching by accepting or rejecting arriving edges and possibly discarding previously accepted ones. We prove a new upper bound of 0.5661 on the competitive ratio achievable for the problem. This bound applies to arbitrary randomized algorithms, bipartite graphs and if we allow the algorithm to output a fractional solution.
Our result improves upon the strongest previously known upper bound of 2-√2 ≈ 0.585, due to Huang et al. [SODA'19]. Previous hardness constructions relied on edge sequences described by vertex arrivals where each arriving vertex reveals its edges to yet unvaried vertices. Under such sequences, Huang et al. showed that there exists a non-preemptive online algorithm with competitive ratio ∼0.567 (or 2-√2 for fractional solutions). Consequently, our hardness construction is the first result which shows hardness for instances where the optimal algorithm employs preemption.

Cite As Get BibTex

Peter Kiss and Mohammad Sharifi. Online Preemptive Matching Revisited. In 53rd International Colloquium on Automata, Languages, and Programming (ICALP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 374, pp. 128:1-128:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.ICALP.2026.128

Author Details

Peter Kiss
  • Faculty of Computer Science, University of Vienna, Austria
Mohammad Sharifi
  • Sharif University of Technology, Tehran, Iran

Funding

  • Kiss, Peter: This research was funded in whole or in part by the Austrian Science Fund (FWF) 10.55776/ESP6088024.

Acknowledgements

The authors would like to thank Sayan Bhattacharya, Thatchaphol Saranurak and Aaron Bernstein for helpful discussions.

References

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