In online metric matching on the line, n requests appear one by one and have to be matched immediately and irrevocably to a given set of servers, all located on the real line. The goal is to minimize the sum of distances between the requests and their assigned servers. The best known online algorithm achieves a competitive ratio of \(\Theta (\log n)\) , leaving a gap to the best-known lower bound of \(\Omega (\sqrt{\log n})\) . In this work, we approach the problem in a recourse model where online decisions can be partially revised, allowing for the reassignment of previously matched edges. In contrast to the traditional online setting, we show that with an amortized recourse budget of \(O(\log n)\) , we can obtain an O(1)-competitive algorithm for online metric matching on the line. This is one of the first non-trivial results for metric matching with recourse. Additionally, for so-called alternating instances, where no more than one request lies between two servers, we achieve a near-optimal result. Specifically, we give a simple algorithm that is \((1+\varepsilon )\) -competitive and reassigns any request at most \(O(\frac{1}{\varepsilon ^2})\) times. This special case is particularly noteworthy, as a lower bound of \(\Omega (\log n)\) , constructed using such instances, applies to a broad class of online algorithms, including all deterministic algorithms studied in the literature.
