Papers
Topics
Authors
Recent
Search
2000 character limit reached

Vertex-Coloring Edge-Weighting: Kernelization and Generalization

Published 23 Sep 2026 in cs.DS, cs.CC, and cs.DM | (2609.27719v1)

Abstract: An edge weighting of a graph induces a coloring of its vertices in which the color of a vertex is the total weight of the edges incident with it. Such an edge weighting is proper if adjacent vertices always receive distinct colors. Deciding whether a graph admits a proper weighting is known to be NP-complete for the weight set 0,1{0,1}, and also for 1,2{1,2}. In recent work (arXiv:2604.12363) we showed that both problems are FPT parameterized by the vertex cover number kk, but it was open -- to the best of our knowledge -- whether either parameterized problem had a polynomial kernel. In this work, we show that both problems have polynomial kernels when parameterized by kk. We also show that both problems are W[1]-hard parameterized by treedepth, answering another question from our earlier work. We then study the pre-weighted versions of the two problems, in which the weights of some edges are fixed in advance, and the task is to extend the assignment to a proper weighting of the whole graph. We show that both pre-weighted problems are FPT parameterized by the vertex cover number kk. For the 1,2{1,2} version the running time is 2<sup>O(k</sup>log⁡k)⋅n2<sup>{O(k</sup> \log k)} \cdot n; for the 0,1{0,1} version we obtain the same running time when every pre-weight is $1$, and a slower FPT algorithm in the general case. We also show that both pre-weighted problems are W[1]-hard parameterized by either of (i) the feedback vertex set number or (ii) the treedepth of the input graph. Since a graph with no pre-assigned weights is a special case, our algorithms for the pre-weighted versions solve the two original problems as well, in time 2<sup>O(k</sup>log⁡k)⋅n2<sup>{O(k</sup> \log k)} \cdot n, significantly improving on the bound of 2<sup>O(k<sup>4)</sup></sup>⋅n<sup>O(1)2<sup>{O(k<sup>4)}</sup></sup> \cdot n<sup>{O(1)} from our earlier work.

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Tweets

Sign up for free to view the 1 tweet with 0 likes about this paper.