License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.SoCG.2020.45
URN: urn:nbn:de:0030-drops-122034
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/12203/
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Fox, Kyle ; Lu, Jiashuai

A Near-Linear Time Approximation Scheme for Geometric Transportation with Arbitrary Supplies and Spread

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LIPIcs-SoCG-2020-45.pdf (0.6 MB)

Abstract

The geometric transportation problem takes as input a set of points P in d-dimensional Euclidean space and a supply function μ : P → ℝ. The goal is to find a transportation map, a non-negative assignment τ : P × P → ℝ_{≥ 0} to pairs of points, so the total assignment leaving each point is equal to its supply, i.e., ∑_{r ∈ P} τ(q, r) - ∑_{p ∈ P} τ(p, q) = μ(q) for all points q ∈ P. The goal is to minimize the weighted sum of Euclidean distances for the pairs, ∑_{(p, q) ∈ P × P} τ(p, q) ⋅ ||q - p||₂.
We describe the first algorithm for this problem that returns, with high probability, a (1 + ε)-approximation to the optimal transportation map in O(n poly(1 / ε) polylog n) time. In contrast to the previous best algorithms for this problem, our near-linear running time bound is independent of the spread of P and the magnitude of its real-valued supplies.

BibTeX - Entry

@InProceedings{fox_et_al:LIPIcs:2020:12203,
  author =	{Kyle Fox and Jiashuai Lu},
  title =	{{A Near-Linear Time Approximation Scheme for Geometric Transportation with Arbitrary Supplies and Spread}},
  booktitle =	{36th International Symposium on Computational Geometry (SoCG 2020)},
  pages =	{45:1--45:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-143-6},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{164},
  editor =	{Sergio Cabello and Danny Z. Chen},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12203},
  URN =		{urn:nbn:de:0030-drops-122034},
  doi =		{10.4230/LIPIcs.SoCG.2020.45},
  annote =	{Keywords: Transportation map, earth mover’s distance, shape matching, approximation algorithms}
}

Keywords: Transportation map, earth mover’s distance, shape matching, approximation algorithms
Collection: 36th International Symposium on Computational Geometry (SoCG 2020)
Issue Date: 2020
Date of publication: 08.06.2020

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