Directed disjoint paths remains W[1]-hard on acyclic digraphs without large grid minors
Ken-ichi Kawarabayashi, Nicola Lorenz, Marcelo Garlet Milani, Jacob Stegemann

TL;DR
This paper proves that the Directed Disjoint Paths problem remains W[1]-hard on acyclic digraphs even under various structural restrictions, highlighting the problem's computational difficulty despite simplified graph conditions.
Contribution
The authors strengthen existing hardness results by showing W[1]-hardness persists on acyclic digraphs with several structural constraints, including absence of large grid minors and bounded ear-anonymity.
Findings
W[1]-hardness holds for all congestion levels c ≥ 1 on acyclic digraphs.
Hardness persists even when the graph excludes large grid minors and tournaments.
Edge-congestion variant remains W[1]-hard under degree and minor exclusion constraints.
Abstract
In the Vertex Disjoint Paths with Congestion problem, the input consists of a digraph , an integer and pairs of vertices , and the task is to find a set of paths connecting each to its corresponding , whereas each vertex of appears in at most many paths. The case where is known to be NP-complete even if [Fortune, Hopcroft and Wyllie, 1980] on general digraphs and is W[1]-hard with respect to (excluding the possibility of an -time algorithm under standard assumptions) on acyclic digraphs [Slivkins, 2010]. The proof of [Slivkins, 2010] can also be adapted to show W[1]-hardness with respect to for every congestion . We strengthen the existing hardness result by showing that the problem remains W[1]-hard for every congestion even if: - the input digraph is acyclic, - does not…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Graph Theory Research · Interconnection Networks and Systems · Complexity and Algorithms in Graphs
