In the online metric traveling salesperson problem, n points of a metric space arrive one by one and have to be placed (immediately and irrevocably) into empty cells of a size-n array. The goal is to minimize the sum of distances between consecutive points in the array. This problem was introduced by Abrahamsen, Bercea, Beretta, Klausen, and Kozma [ESA'24] as a generalization of the online sorting problem, which was introduced by Aamand, Abrahamsen, Beretta, and Kleist [SODA'23] as a tool in their study of online geometric packing problems. Online metric TSP has been studied for a range of fixed metric spaces. For 1-dimensional Euclidean space, the problem is equivalent to online sorting, where an optimal competitive ratio of Θ(√n) is known. For d-dimensional Euclidean space, the best-known upper bound is O(2^d √{dn log n}), leaving a gap to the Ω(√n) lower bound. Finally, for the uniform metric, where all distances are 0 or 1, the optimal competitive ratio is known to be Θ(log n). We study the problem for a general metric space, presenting an algorithm with competitive ratio O(√n). In particular, we close the gap for d-dimensional Euclidean space, completely removing the dependence on dimension. One might hope to simultaneously guarantee competitive ratio O(√n) in general and O(log n) for the uniform metric, but we show that this is impossible.
@InProceedings{bertram:LIPIcs.ESA.2025.80, author = {Bertram, Christian}, title = {{Online Metric TSP}}, booktitle = {33rd Annual European Symposium on Algorithms (ESA 2025)}, pages = {80:1--80:9}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-395-9}, ISSN = {1868-8969}, year = {2025}, volume = {351}, editor = {Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.80}, URN = {urn:nbn:de:0030-drops-245485}, doi = {10.4230/LIPIcs.ESA.2025.80}, annote = {Keywords: online algorithm, metric space, TSP} }
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