Quasi-polynomial time approximation schemes for packing and covering problems in planar graphs

TL;DR

This paper develops quasi-polynomial time approximation schemes for two complex optimization problems in planar graphs, extending geometric problem techniques to a combinatorial graph setting with near-optimal solutions.

Contribution

It introduces QPTAS algorithms for packing and covering problems in planar graphs, adapting geometric approximation techniques to a combinatorial framework.

Findings

Achieves $(1+psilon)$-approximate solutions in quasi-polynomial time.

Provides a combinatorial approach to geometric approximation techniques.

Extends applicability of geometric methods to planar graph problems.

Abstract

We consider two optimization problems in planar graphs. In Maximum Weight Independent Set of Objects we are given a graph $G$ and a family $\mathcal{D}$ of objects, each being a connected subgraph of $G$ with a prescribed weight, and the task is to find a maximum-weight subfamily of $\mathcal{D}$ consisting of pairwise disjoint objects. In Minimum Weight Distance Set Cover we are given an edge-weighted graph $G$, two sets $\mathcal{D},\mathcal{C}$ of vertices of $G$, where vertices of $\mathcal{D}$ have prescribed weights, and a nonnegative radius $r$. The task is to find a minimum-weight subset of $\mathcal{D}$ such that every vertex of $\mathcal{C}$ is at distance at most $r$ from some selected vertex. Via simple reductions, these two problems generalize a number of geometric optimization tasks, notably Maximum Weight Independent Set for polygons in the plane and Weighted Geometric Set Cover for unit disks and unit squares. We present quasi-polynomial time approximation schemes (QPTASs) for both of the above problems in planar graphs: given an accuracy parameter $\epsilon>0$ we can compute a solution whose weight is within multiplicative factor of $(1+\epsilon)$ from the optimum in time $2^{\mathrm{poly}(1/\epsilon,\log |\mathcal{D}|)}\cdot n^{\mathcal{O}(1)}$, where $n$ is the number of vertices of the input graph. Our main technical contribution is to transfer the techniques used for recursive approximation schemes for geometric problems due to Adamaszek, Har-Peled, and Wiese to the setting of planar graphs. In particular, this yields a purely combinatorial viewpoint on these methods.