Faster Approximation Algorithms for Restricted Shortest Paths in Directed Graphs
Vikrant Ashvinkumar, Aaron Bernstein, Adam Karczmarz

TL;DR
This paper introduces faster randomized approximation algorithms for the restricted shortest paths problem in directed graphs, achieving near-quadratic and sub-quadratic time complexities for dense and sparse graphs respectively, solving a long-standing open problem.
Contribution
It provides the first sub-$mn$ time bicriteria approximation algorithms for directed graphs, improving upon decades-old methods and addressing an open problem in the field.
Findings
Algorithms run in near-quadratic time for dense graphs.
Algorithms run in sub-quadratic time for sparse graphs.
Achieves a positive answer to the open problem for directed graphs.
Abstract
In the restricted shortest paths problem, we are given a graph whose edges are assigned two non-negative weights: lengths and delays, a source , and a delay threshold . The goal is to find, for each target , the length of the shortest -path whose total delay is at most . While this problem is known to be NP-hard [Garey and Johnson, 1979] -approximate algorithms running in time [Goel et al., INFOCOM'01; Lorenz and Raz, Oper. Res. Lett.'01] given more than twenty years ago have remained the state-of-the-art for directed graphs. An open problem posed by [Bernstein, SODA'12] -- who gave a randomized time bicriteria -approximation algorithm for undirected graphs -- asks if there is similarly an time approximation scheme for directed graphs. We show two randomized bicriteria…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Graph Theory and Algorithms · Data Management and Algorithms
