English

Low Treewidth Embeddings of Planar and Minor-Free Metrics

Data Structures and Algorithms 2022-03-30 v1

Abstract

Cohen-Addad, Filtser, Klein and Le [FOCS'20] constructed a stochastic embedding of minor-free graphs of diameter DD into graphs of treewidth Oϵ(logn)O_{\epsilon}(\log n) with expected additive distortion +ϵD+\epsilon D. Cohen-Addad et al. then used the embedding to design the first quasi-polynomial time approximation scheme (QPTAS) for the capacitated vehicle routing problem. Filtser and Le [STOC'21] used the embedding (in a different way) to design a QPTAS for the metric Baker's problems in minor-free graphs. In this work, we devise a new embedding technique to improve the treewidth bound of Cohen-Addad et al. exponentially to Oϵ(loglogn)2O_{\epsilon}(\log\log n)^2. As a corollary, we obtain the first efficient PTAS for the capacitated vehicle routing problem in minor-free graphs. We also significantly improve the running time of the QPTAS for the metric Baker's problems in minor-free graphs from nOϵ(log(n))n^{O_{\epsilon}(\log(n))} to nOϵ(loglog(n))3n^{O_{\epsilon}(\log\log(n))^3}. Applying our embedding technique to planar graphs, we obtain a deterministic embedding of planar graphs of diameter DD into graphs of treewidth O((loglogn)2)/ϵ)O((\log\log n)^2)/\epsilon) and additive distortion +ϵD+\epsilon D that can be constructed in nearly linear time. Important corollaries of our result include a bicriteria PTAS for metric Baker's problems and a PTAS for the vehicle routing problem with bounded capacity in planar graphs, both run in almost-linear time. The running time of our algorithms is significantly better than previous algorithms that require quadratic time. A key idea in our embedding is the construction of an (exact) emulator for tree metrics with treewidth O(loglogn)O(\log\log n) and hop-diameter O(loglogn)O(\log \log n). This result may be of independent interest.

Keywords

Cite

@article{arxiv.2203.15627,
  title  = {Low Treewidth Embeddings of Planar and Minor-Free Metrics},
  author = {Arnold Filtser and Hung Le},
  journal= {arXiv preprint arXiv:2203.15627},
  year   = {2022}
}