,
Ulrike Schmidt-Kraepelin
,
Andree-Ovidiu Ștef
Creative Commons Attribution 4.0 International license
Computing a minimum-weight perfect matching for a point set P in Euclidean space is a classic geometric optimization problem. We consider the problem in a dynamic setting, where pairs of points may be added to or removed from the set P. Our focus is on maintaining an approximately optimal solution without making too many changes to the solution. More precisely, we are interested in k-stable algorithms, which change at most k edges in the matching after each update to the set P. In other words, we consider an online setting (with insertions and deletions) with bounded recourse. We study trade-offs between the stability of the algorithm and the approximation ratio of the maintained solution for point sets in ℝ¹. First, we present an O(√n)-stable algorithm that maintains a 2-approximation, which we show to be optimal among all algorithms with sublinear stability. Second, we prove that any o(log n)-stable algorithm has unbounded approximation ratio. Our lower bounds hold even in the insertion-only case, while our algorithm works in the fully dynamic case. Moreover, our lower bounds also hold for the bipartite variant of the problem.
@InProceedings{deberg_et_al:LIPIcs.ESA.2026.27,
author = {de Berg, Mark and Schmidt-Kraepelin, Ulrike and Ștef, Andree-Ovidiu},
title = {{On the Stability of Minimum-Weight Perfect Matching on the Line}},
booktitle = {34th Annual European Symposium on Algorithms (ESA 2026)},
pages = {27:1--27:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-445-1},
ISSN = {1868-8969},
year = {2026},
volume = {388},
editor = {Bille, Philip and Pettie, Seth and Storandt, Sabine},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2026.27},
URN = {urn:nbn:de:0030-drops-271632},
doi = {10.4230/LIPIcs.ESA.2026.27},
annote = {Keywords: Euclidean matching, stable approximation algorithms, dynamic algorithms, online algorithms, bounded recourse}
}