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Optimal Online Bipartite Matching in Degree-2 Graphs

Published: November 20, 2025 | arXiv ID: 2511.16025v1

By: Amey Bhangale, Arghya Chakraborty, Prahladh Harsha

Potential Business Impact:

Finds better ways to match things online.

Business Areas:
A/B Testing Data and Analytics

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.

Country of Origin
🇺🇸 United States

Page Count
18 pages

Category
Computer Science:
Data Structures and Algorithms