We study the classical Node-Disjoint Paths (NDP) problem: given an n-vertex graph G and a collection M = {(s1, t1), . . . , (s k , t k )} of pairs of vertices of G called demand pairs, find a maximum-cardinality set of node-disjoint paths connecting the demand pairs. NDP is one of the most basic routing problems, that has been studied extensively. Despite this, there are still wide gaps in our understanding of its approximability: the best currently known upper bound of O( √ n) on its approximation ratio is achieved via a simple greedy algorithm, while the best current negative result shows that the problem does not have a better than Ω(log 1/2−δ n)-approximation for any constant δ, under standard complexity assumptions. Even for planar graphs no better approximation algorithms are known, and to the best of our knowledge, the best negative bound is APX-hardness. Perhaps the biggest obstacle to obtaining better approximation algorithms for NDP is that most currently known approximation algorithms for this type of problems rely on the standard multicommodity flow relaxation, whose integrality gap is Ω( √ n) for NDP, even in planar graphs. In this paper, we break the barrier of O( √ n) on the approximability of NDP in planar graphs and obtain anÕ(n 9/19 )approximation. We introduce a new linear programming relaxation of the problem, and a number of new techniques, that we hope will be helpful in designing more powerful algorithms for this and related problems.
Hence theÕ(n 9/19 )-approximation algorithm for NDP with planar supply graphs REF implies the same approximation ratio for EDP with G + H planar.
Improved approximation for node-disjoint paths in planar graphs
STOC 2016
Mathematics Computer Science