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Approximation Schemes for Routing Problems in Minor-Free Metrics

Arnold Filtser
Hung Le
Philip N. Klein
IEEE Symposium on Foundations of Computer Science (FOCS'20) (2020)
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Understanding the structure of minor-free metrics, namely shortest path metrics obtained over a weighted graph excluding a fixed minor, has been an important research direction since the fundamental work of Robertson and Seymour. A fundamental idea that helps both to understand the structural properties of these metrics and lead to strong algorithmic results is to construct a ``small-complexity'' graph that approximately preserves distances between pairs of points of the metric. We show the two following structural results for minor-free metrics: _ Construction of a \emph{light} subset spanner. Given a subset of vertices called terminals, and $\epsilon$, in polynomial time we construct a subgraph that preserves all pairwise distances between terminals up to a multiplicative $1+\epsilon$ factor, of total weight at most $O_{\epsilon}(1)$ times the weight of the minimal Steiner tree spanning the terminals. _ Construction of a stochastic metric embedding into low treewidth graphs with expected additive distortion $\epsilon D$. Namely, given a minor free graph $G=(V,E,w)$ of diameter $D$, and parameter $\epsilon$, we construct a distribution $\mathcal{D}$ over dominating metric embeddings into treewidth-$O_{\epsilon}(\log n)$ graphs such that $\forall u,v\in V$, $\mathbb{E}_{f\sim\mathcal{D}}[d_H(f(u),f(v))]\le d_G(u,v)+\epsilon D$. One of our important technical contributions is a novel framework that allows us to reduce \emph{both problems} to problems on simpler graphs of \emph{bounded diameter} that we solve using a new decomposition. Our results have the following algorithmic consequences: (1) the first efficient approximation scheme for subset TSP in minor-free metrics; (2) the first approximation scheme for vehicle routing with bounded capacity in minor-free metrics; (3) the first efficient approximation scheme for vehicle routing with bounded capacity on bounded genus metrics.