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 a graph G in which the edges might have different lengths, 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. We note that a QPTAS for Maximum Weight Independent Set of Objects would follow from existing work. However, our main contribution is to provide a unified framework that works for both problems in both a planar and geometric setting and to transfer the techniques used for recursive approximation schemes for geometric problems due to Adamaszek and Wiese (in Proceedings of the FOCS 2013, IEEE, 2013; in Proceedings of the SODA 2014, SIAM, 2014) and Har-Peled and Sariel (in Proceedings of the SOCG 2014, SIAM, 2014) to the setting of planar graphs. In particular, this yields a purely combinatorial viewpoint on these methods as a phenomenon in planar graphs.
Highlights
Independent Set and Dominating Set are fundamental optimization problems on graphs
Classic layering techniques can be applied to show that both problems admit EPTASs, i.e., (1 + )-approximation algorithms with a running time of f (1/ )nO(1) for some function f, and fpt algorithms for the parameterization by the solution size, i.e., for a parameter k, algorithms running in time f (k)nO(1) that find a best solution among those of size at most k
The Minimum Weight Distance Set Cover problem in planar graphs admits a quasi-polynomial time approximation schemes (QPTASs) with running time 2poly(1/,log N) · nO(1), where n is the vertex count of the input graph and N = |D| is the number of vertices allowed to be selected to the solution
Summary
Independent Set and Dominating Set are fundamental optimization problems on graphs. Given a graph G where each vertex v has a weight w(v), in Independent Set one seeks to find a vertex subset I ⊆ V (G) of maximum possible weight such that no two vertices in I are adjacent, whereas in Dominating Set one searches for a vertex subset D of minimum possible weight such that each vertex v ∈ V (G) is contained in D or adjacent to a vertex in D. The Minimum Weight Distance Set Cover problem in planar graphs admits a QPTAS with running time 2poly(1/ ,log N) · nO(1), where n is the vertex count of the input graph and N = |D| is the number of vertices allowed to be selected to the solution. The heart of our technical contribution is to show that for any instance of the above problems there is a set of candidate separators of polynomial size such that one of them splits the given problem in a balanced way and intersects only a tiny fraction of the given solution The latter is important since the intersected objects will be lost (in the case of MWISO) or might be paid twice (in the case of MWDSC) and we need to bound their total weight by OPT. In the full version we explain how to derive the mentioned results from our theorems
Published Version
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