Approximation Algorithms for Min-Distance Problems
We study fundamental graph parameters such as the Diameter and Radius in directed graphs, when distances are measured using a somewhat unorthodox but natural measure: the distance between u and v is the minimum of the shortest path distances from u to v and from v to u. The center node in a graph under this measure can for instance represent the optimal location for a hospital to ensure the fastest medical care for everyone, as one can either go to the hospital, or a doctor can be sent to help.
By computing All-Pairs Shortest Paths, all pairwise distances and thus the parameters we study can be computed exactly in O~(mn) time for directed graphs on n vertices, m edges and nonnegative edge weights. Furthermore, this time bound is tight under the Strong Exponential Time Hypothesis [Roditty-Vassilevska W. STOC 2013] so it is natural to study how well these parameters can be approximated in O(mn^{1-epsilon}) time for constant epsilon>0. Abboud, Vassilevska Williams, and Wang [SODA 2016] gave a polynomial factor approximation for Diameter and Radius, as well as a constant factor approximation for both problems in the special case where the graph is a DAG. We greatly improve upon these bounds by providing the first constant factor approximations for Diameter, Radius and the related Eccentricities problem in general graphs. Additionally, we provide a hierarchy of algorithms for Diameter that gives a time/accuracy trade-off.
fine-grained complexity
graph algorithms
diameter
radius
eccentricities
Mathematics of computing~Graph algorithms
46:1-46:14
Track A: Algorithms, Complexity and Games
https://arxiv.org/abs/1904.11606
The authors would like to thank the members of the MIT course 6.S078 open problem sessions, especially Thuy-Duong Vuong, Robin Hui, and Ali Vakilian. These sessions were organized by Erik Demaine, Ryan Williams, and Virginia Vassilevska Williams.
Mina
Dalirrooyfard
Mina Dalirrooyfard
MIT, Cambridge, MA, USA
Virginia Vassilevska
Williams
Virginia Vassilevska Williams
MIT, Cambridge, MA, USA
Nikhil
Vyas
Nikhil Vyas
MIT, Cambridge, MA, USA
Nicole
Wein
Nicole Wein
MIT, Cambridge, MA, USA
Yinzhan
Xu
Yinzhan Xu
MIT, Cambridge, MA, USA
Yuancheng
Yu
Yuancheng Yu
MIT, Cambridge, MA, USA
10.4230/LIPIcs.ICALP.2019.46
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Mina Dalirrooyfard, Virginia Vassilevska Williams, Nikhil Vyas, Nicole Wein, Yinzhan Xu, and Yuancheng Yu
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