Almost Polynomial Hardness of Node-Disjoint Paths in Grids
Julia Chuzhoy, David H. K. Kim, Rachit Nimavat

TL;DR
This paper establishes near-polynomial hardness of approximating the Node-Disjoint Paths problem in grid graphs, significantly advancing understanding of its computational difficulty and close to resolving an open question.
Contribution
It proves new hardness of approximation bounds for NDP in grid graphs, nearly matching the best known upper bounds, and extends results to related Edge-Disjoint Paths problems.
Findings
NDP is $2^{ ext{polylogarithmic}}$-hard to approximate in grid graphs.
NDP is $n^{ ext{inverse polylog}}$-hard to approximate under certain complexity assumptions.
Results apply to wall graphs and the Edge-Disjoint Paths problem.
Abstract
In the classical Node-Disjoint Paths (NDP) problem, we are given an -vertex graph , and a collection of pairs of its vertices, called source-destination, or demand pairs. The goal is to route as many of the demand pairs as possible, where to route a pair we need to select a path connecting it, so that all selected paths are disjoint in their vertices. The best current algorithm for NDP achieves an -approximation, while, until recently, the best negative result was a factor -hardness of approximation, for any constant , unless . In a recent work, the authors have shown an improved -hardness of approximation for NDP, unless , even if the underlying graph is a subgraph of a grid graph, and all…
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