Optimal Online Bipartite Matching in Degree-2 Graphs

Fuente: arXiv
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Autores principales: Bhangale, Amey, Chakraborty, Arghya, Harsha, Prahladh
Formato: Preprint
Publicado: 2025
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author Bhangale, Amey
Chakraborty, Arghya
Harsha, Prahladh
author_facet Bhangale, Amey
Chakraborty, Arghya
Harsha, Prahladh
contents Online bipartite matching is a classical problem in online algorithms and we know that both the deterministic fractional and randomized integral online matchings achieve the same competitive ratio of $1-\frac{1}{e}$. In this work, we study classes of graphs where the online degree is restricted to $2$. As expected, one can achieve a competitive ratio of better than $1-\frac{1}{e}$ in both the deterministic fractional and randomized integral cases, but surprisingly, these ratios are not the same. It was already known that for fractional matching, a $0.75$ competitive ratio algorithm is optimal. We show that the folklore \textsc{Half-Half} algorithm achieves a competitive ratio of $η\approx 0.717772\dots$ and more surprisingly, show that this is optimal by giving a matching lower-bound. This yields a separation between the two problems: deterministic fractional and randomized integral, showing that it is impossible to obtain a perfect rounding scheme.
format Preprint
id arxiv_https___arxiv_org_abs_2511_16025
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimal Online Bipartite Matching in Degree-2 Graphs
Bhangale, Amey
Chakraborty, Arghya
Harsha, Prahladh
Data Structures and Algorithms
68W20, 68R10, 90C27
Online bipartite matching is a classical problem in online algorithms and we know that both the deterministic fractional and randomized integral online matchings achieve the same competitive ratio of $1-\frac{1}{e}$. In this work, we study classes of graphs where the online degree is restricted to $2$. As expected, one can achieve a competitive ratio of better than $1-\frac{1}{e}$ in both the deterministic fractional and randomized integral cases, but surprisingly, these ratios are not the same. It was already known that for fractional matching, a $0.75$ competitive ratio algorithm is optimal. We show that the folklore \textsc{Half-Half} algorithm achieves a competitive ratio of $η\approx 0.717772\dots$ and more surprisingly, show that this is optimal by giving a matching lower-bound. This yields a separation between the two problems: deterministic fractional and randomized integral, showing that it is impossible to obtain a perfect rounding scheme.
title Optimal Online Bipartite Matching in Degree-2 Graphs
topic Data Structures and Algorithms
68W20, 68R10, 90C27
url https://arxiv.org/abs/2511.16025