25 research outputs found
A Gap-{ETH}-Tight Approximation Scheme for Euclidean {TSP}
We revisit the classic task of finding the shortest tour of points in -dimensional Euclidean space, for any fixed constant . We determine the optimal dependence on in the running time of an algorithm that computes a -approximate tour, under a plausible assumption. Specifically, we give an algorithm that runs in time. This improves the previously smallest dependence on in the running time of the algorithm by Rao and Smith (STOC 1998). We also show that a algorithm would violate the Gap-Exponential Time Hypothesis (Gap-ETH). Our new algorithm builds upon the celebrated quadtree-based methods initially proposed by Arora (J. ACM 1998), but it adds a simple new idea that we call \emph{sparsity-sensitive patching}. On a high level this lets the granularity with which we simplify the tour depend on how sparse it is locally. Our approach is (arguably) simpler than the one by Rao and Smith since it can work without geometric spanners. We demonstrate the technique extends easily to other problems, by showing as an example that it also yields a Gap-ETH-tight approximation scheme for Rectilinear Steiner Tree
strip
We investigate how the complexity of Euclidean TSP for point sets inside the strip depends on the strip width . We obtain two main results. First, for the case where the points have distinct integer -coordinates, we prove that a shortest bitonic tour (which can be computed in time using an existing algorithm) is guaranteed to be a shortest tour overall when , a bound which is best possible. Second, we present an algorithm that is fixed-parameter tractable with respect to . More precisely, our algorithm has running time for sparse point sets, where each rectangle inside the strip contains points. For random point sets, where the points are chosen uniformly at random from the rectangle~, it has an expected running time of
The homogeneous broadcast problem in narrow and wide strips
Let be a set of nodes in a wireless network, where each node is modeled as a point in the plane, and let be a given source node. Each node can transmit information to all other nodes within unit distance, provided is activated. The (homogeneous) broadcast problem is to activate a minimum number of nodes such that in the resulting directed communication graph, the source can reach any other node. We study the complexity of the regular and the hop-bounded version of the problem (in the latter, must be able to reach every node within a specified number of hops), with the restriction that all points lie inside a strip of width . We almost completely characterize the complexity of both the regular and the hop-bounded versions as a function of the strip width
Subexponential Parameterized Directed Steiner Network Problems on Planar Graphs: A Complete Classification
In the Directed Steiner Network problem, the input is a directed graph G, asubset T of k vertices of G called the terminals, and a demand graph D on T.The task is to find a subgraph H of G with the minimum number of edges suchthat for every edge (s,t) in D, the solution H contains a directed s to t path.In this paper we investigate how the complexity of the problem depends on thedemand pattern when G is planar. Formally, if \mathcal{D} is a class ofdirected graphs closed under identification of vertices, then the\mathcal{D}-Steiner Network (\mathcal{D}-SN) problem is the special case wherethe demand graph D is restricted to be from \mathcal{D}. For general graphs,Feldmann and Marx [ICALP 2016] characterized those families of demand graphswhere the problem is fixed-parameter tractable (FPT) parameterized by thenumber k of terminals. They showed that if \mathcal{D} is a superset of one ofthe five hard families, then \mathcal{D}-SN is W[1]-hard parameterized by k,otherwise it can be solved in time f(k)n^{O(1)}. For planar graphs an interesting question is whether the W[1]-hard cases canbe solved by subexponential parameterized algorithms. Chitnis et al. [SICOMP2020] showed that, assuming the ETH, there is no f(k)n^{o(k)} time algorithmfor the general \mathcal{D}-SN problem on planar graphs, but the special casecalled Strongly Connected Steiner Subgraph can be solved in time f(k)n^{O(\sqrt{k})} on planar graphs. We present a far-reaching generalization andunification of these two results: we give a complete characterization of thebehavior of every -SN problem on planar graphs. We show thatassuming ETH, either the problem is (1) solvable in time 2^{O(k)}n^{O(1)}, andnot in time 2^{o(k)}n^{O(1)}, or (2) solvable in time f(k)n^{O(\sqrt{k})}, butnot in time f(k)n^{o(\sqrt{k})}, or (3) solvable in time f(k)n^{O(k)}, but notin time f(k)n^{o({k})}.<br
Online Search for a Hyperplane in High-Dimensional Euclidean Space
We consider the online search problem in which a server starting at the origin of a -dimensional Euclidean space has to find an arbitrary hyperplane. The best-possible competitive ratio and the length of the shortest curve from which each point on the -dimensional unit sphere can be seen are within a constant factor of each other. We show that this length is in
On the Approximability of the Traveling Salesman Problem with Line Neighborhoods
We study the variant of the Euclidean Traveling Salesman problem where instead of a set of points, we are given a set of lines as input, and the goal is to find the shortest tour that visits each line. The best known upper and lower bounds for the problem in , with , are -hardness and an -approximation algorithm which is based on a reduction to the group Steiner tree problem. We show that TSP with lines in is APX-hard for any . More generally, this implies that TSP with -dimensional flats does not admit a PTAS for any unless , which gives a complete classification of the approximability of these problems, as there are known PTASes for (i.e., points) and (hyperplanes). We are able to give a stronger inapproximability factor for by showing that TSP with lines does not admit a -approximation in dimensions under the unique games conjecture. On the positive side, we leverage recent results on restricted variants of the group Steiner tree problem in order to give an -approximation algorithm for the problem, albeit with a running time of
A framework for ETH-Tight algorithms and lower bounds in geometric intersection graphs
We give an algorithmic and lower-bound framework that facilitates the construction of subexponential algorithms and matching conditional complexity bounds. It can be applied to a wide range of geometric intersection graphs (intersections of similarly sized fat objects), yielding algorithms with running time 2O(n1−1/d) for any fixed dimension d ≥ 2 for many well known graph problems, including Independent Set, r-Dominating Set for constant r, and Steiner Tree. For most problems, we get improved running times compared to prior work; in some cases, we give the first known subexponential algorithm in geometric intersection graphs. Additionally, most of the obtained algorithms work on the graph itself, i.e., do not require any geometric information. Our algorithmic framework is based on a weighted separator theorem and various treewidth techniques. The lower bound framework is based on a constructive embedding of graphs into d-dimensional grids, and it allows us to derive matching 2Ω(n1−1/d) lower bounds under the Exponential Time Hypothesis even in the much more restricted class of d-dimensional induced grid graphs