Quasi-polynomial time approximation schemes for packing and covering problems in planar graphs
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We consider two optimization problems in planar graphs. In Maximum Weight Independent Set of Objects we are given a graph G and a family 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 D consisting of pairwise disjoint objects. In Minimum Weight Distance Set Cover we are given an edge-weighted graph G, two sets D,C of vertices of G, where vertices of D have prescribed weights, and a nonnegative radius r. The task is to find a minimum-weight subset of D such that every vertex of 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 ϵ>0 we can compute a solution whose weight is within multiplicative factor of (1+ϵ) from the optimum in time 2^poly(1/ϵ, |D|)· n^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.
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