We present the first nearlineartime algorithm that computes a (1+ε)approximation of the diameter of a weighted unitdisk graph of n vertices. Our algorithm requires O(n log^2 n)
time for any constant ε>0, so we considerably improve upon the nearO(n^{3/2})time algorithm of Gao and Zhang (2005). Using similar ideas we develop (1+ε)approximate \emph{distance oracles} of O(1) query time with a likewise improvement in the preprocessing time, specifically from near O(n^{3/2}) to O(n log^3 n). We also obtain similar new results for a number of related problems in the weighted unitdisk graph metric such as the radius and the bichromatic closest pair.
As a further application we employ our distance oracle, along with additional ideas, to solve the (1+ε)approximate \emph{allpairs boundedleg shortest paths\/} (apBLSP) problem for a set of n planar points. Our data structure requires O(n^2 log n) space, O(loglog n) query time, and nearly O(n^{2.579}) preprocessing time for any constant ε>0, and is the first that breaks the nearcubic preprocessing time bound given by Roditty and Segal (2011).
more »
« less
Approximation Algorithm for Norm Multiway Cut
We consider variants of the classic Multiway Cut problem. Multiway Cut asks to partition a graph G into k parts so as to separate k given terminals. Recently, Chandrasekaran and Wang (ESA 2021) introduced l_pnorm Multiway Cut, a generalization of the problem, in which the goal is to minimize the l_p norm of the edge boundaries of k parts. We provide an O(log^{1/2} n log^{1/2 + 1/p} k) approximation algorithm for this problem, improving upon the approximation guarantee of O(log^{3/2} n log^{1/2} k) due to Chandrasekaran and Wang.
We also introduce and study Norm Multiway Cut, a further generalization of Multiway Cut. We assume that we are given access to an oracle, which answers certain queries about the norm. We present an O(log^{1/2} n log^{7/2} k) approximation algorithm with a weaker oracle and an O(log^{1/2} n log^{5/2} k) approximation algorithm with a stronger oracle. Additionally, we show that without any oracle access, there is no n^{1/4ε} approximation algorithm for every ε > 0 assuming the Hypergraph DensevsRandom Conjecture.
more »
« less
 NSFPAR ID:
 10518040
 Editor(s):
 Gørtz, Inge Li; FarachColton, Martin; Puglisi, Simon J; Herman, Grzegorz
 Publisher / Repository:
 Schloss Dagstuhl – LeibnizZentrum für Informatik
 Date Published:
 Journal Name:
 Proceedings of the European Symposium on Algorithms
 Subject(s) / Keyword(s):
 Multiway cut Approximation algorithms Theory of computation → Approximation algorithms analysis
 Format(s):
 Medium: X
 Sponsoring Org:
 National Science Foundation
More Like this


null (Ed.)We consider the classical Minimum Balanced Cut problem: given a graph $G$, compute a partition of its vertices into two subsets of roughly equal volume, while minimizing the number of edges connecting the subsets. We present the first {\em deterministic, almostlinear time} approximation algorithm for this problem. Specifically, our algorithm, given an $n$vertex $m$edge graph $G$ and any parameter $1\leq r\leq O(\log n)$, computes a $(\log m)^{r^2}$approximation for Minimum Balanced Cut on $G$, in time $O\left ( m^{1+O(1/r)+o(1)}\cdot (\log m)^{O(r^2)}\right )$. In particular, we obtain a $(\log m)^{1/\epsilon}$approximation in time $m^{1+O(1/\sqrt{\epsilon})}$ for any constant $\epsilon$, and a $(\log m)^{f(m)}$approximation in time $m^{1+o(1)}$, for any slowly growing function $m$. We obtain deterministic algorithms with similar guarantees for the Sparsest Cut and the LowestConductance Cut problems. Our algorithm for the Minimum Balanced Cut problem in fact provides a stronger guarantee: it either returns a balanced cut whose value is close to a given target value, or it certifies that such a cut does not exist by exhibiting a large subgraph of $G$ that has high conductance. We use this algorithm to obtain deterministic algorithms for dynamic connectivity and minimum spanning forest, whose worstcase update time on an $n$vertex graph is $n^{o(1)}$, thus resolving a major open problem in the area of dynamic graph algorithms. Our work also implies deterministic algorithms for a host of additional problems, whose time complexities match, up to subpolynomial in $n$ factors, those of known randomized algorithms. The implications include almostlinear time deterministic algorithms for solving Laplacian systems and for approximating maximum flows in undirected graphs.more » « less

Given a metric space ℳ = (X,δ), a weighted graph G over X is a metric tspanner of ℳ if for every u,v ∈ X, δ(u,v) ≤ δ_G(u,v) ≤ t⋅ δ(u,v), where δ_G is the shortest path metric in G. In this paper, we construct spanners for finite sets in metric spaces in the online setting. Here, we are given a sequence of points (s₁, …, s_n), where the points are presented one at a time (i.e., after i steps, we have seen S_i = {s₁, … , s_i}). The algorithm is allowed to add edges to the spanner when a new point arrives, however, it is not allowed to remove any edge from the spanner. The goal is to maintain a tspanner G_i for S_i for all i, while minimizing the number of edges, and their total weight. Under the L₂norm in ℝ^d for arbitrary constant d ∈ ℕ, we present an online (1+ε)spanner algorithm with competitive ratio O_d(ε^{d} log n), improving the previous bound of O_d(ε^{(d+1)}log n). Moreover, the spanner maintained by the algorithm has O_d(ε^{1d}log ε^{1})⋅ n edges, almost matching the (offline) optimal bound of O_d(ε^{1d})⋅ n. In the plane, a tighter analysis of the same algorithm provides an almost quadratic improvement of the competitive ratio to O(ε^{3/2}logε^{1}log n), by comparing the online spanner with an instanceoptimal spanner directly, bypassing the comparison to an MST (i.e., lightness). As a counterpart, we design a sequence of points that yields a Ω_d(ε^{d}) lower bound for the competitive ratio for online (1+ε)spanner algorithms in ℝ^d under the L₁norm. Then we turn our attention to online spanners in general metrics. Note that, it is not possible to obtain a spanner with stretch less than 3 with a subquadratic number of edges, even in the offline setting, for general metrics. We analyze an online version of the celebrated greedy spanner algorithm, dubbed ordered greedy. With stretch factor t = (2k1)(1+ε) for k ≥ 2 and ε ∈ (0,1), we show that it maintains a spanner with O(ε^{1}logε^{1})⋅ n^{1+1/k} edges and O(ε^{1}n^{1/k}log² n) lightness for a sequence of n points in a metric space. We show that these bounds cannot be significantly improved, by introducing an instance that achieves an Ω(1/k⋅ n^{1/k}) competitive ratio on both sparsity and lightness. Furthermore, we establish the tradeoff among stretch, number of edges and lightness for points in ultrametrics, showing that one can maintain a (2+ε)spanner for ultrametrics with O(ε^{1}logε^{1})⋅ n edges and O(ε^{2}) lightness.more » « less

Given a metric space ℳ = (X,δ), a weighted graph G over X is a metric tspanner of ℳ if for every u,v ∈ X, δ(u,v) ≤ δ_G(u,v) ≤ t⋅ δ(u,v), where δ_G is the shortest path metric in G. In this paper, we construct spanners for finite sets in metric spaces in the online setting. Here, we are given a sequence of points (s₁, …, s_n), where the points are presented one at a time (i.e., after i steps, we have seen S_i = {s₁, … , s_i}). The algorithm is allowed to add edges to the spanner when a new point arrives, however, it is not allowed to remove any edge from the spanner. The goal is to maintain a tspanner G_i for S_i for all i, while minimizing the number of edges, and their total weight. Under the L₂norm in ℝ^d for arbitrary constant d ∈ ℕ, we present an online (1+ε)spanner algorithm with competitive ratio O_d(ε^{d} log n), improving the previous bound of O_d(ε^{(d+1)}log n). Moreover, the spanner maintained by the algorithm has O_d(ε^{1d}log ε^{1})⋅ n edges, almost matching the (offline) optimal bound of O_d(ε^{1d})⋅ n. In the plane, a tighter analysis of the same algorithm provides an almost quadratic improvement of the competitive ratio to O(ε^{3/2}logε^{1}log n), by comparing the online spanner with an instanceoptimal spanner directly, bypassing the comparison to an MST (i.e., lightness). As a counterpart, we design a sequence of points that yields a Ω_d(ε^{d}) lower bound for the competitive ratio for online (1+ε)spanner algorithms in ℝ^d under the L₁norm. Then we turn our attention to online spanners in general metrics. Note that, it is not possible to obtain a spanner with stretch less than 3 with a subquadratic number of edges, even in the offline setting, for general metrics. We analyze an online version of the celebrated greedy spanner algorithm, dubbed ordered greedy. With stretch factor t = (2k1)(1+ε) for k ≥ 2 and ε ∈ (0,1), we show that it maintains a spanner with O(ε^{1}logε^{1})⋅ n^{1+1/k} edges and O(ε^{1}n^{1/k}log² n) lightness for a sequence of n points in a metric space. We show that these bounds cannot be significantly improved, by introducing an instance that achieves an Ω(1/k⋅ n^{1/k}) competitive ratio on both sparsity and lightness. Furthermore, we establish the tradeoff among stretch, number of edges and lightness for points in ultrametrics, showing that one can maintain a (2+ε)spanner for ultrametrics with O(ε^{1}logε^{1})⋅ n edges and O(ε^{2}) lightness.more » « less

Ahn, HeeKap ; Sadakane, Kunihiko (Ed.)In the standard planar kcenter clustering problem, one is given a set P of n points in the plane, and the goal is to select k center points, so as to minimize the maximum distance over points in P to their nearest center. Here we initiate the systematic study of the clustering with neighborhoods problem, which generalizes the kcenter problem to allow the covered objects to be a set of general disjoint convex objects C rather than just a point set P. For this problem we first show that there is a PTAS for approximating the number of centers. Specifically, if r_opt is the optimal radius for k centers, then in n^O(1/ε²) time we can produce a set of (1+ε)k centers with radius ≤ r_opt. If instead one considers the standard goal of approximating the optimal clustering radius, while keeping k as a hard constraint, we show that the radius cannot be approximated within any factor in polynomial time unless P = NP, even when C is a set of line segments. When C is a set of unit disks we show the problem is hard to approximate within a factor of (√{13}√3)(2√3) ≈ 6.99. This hardness result complements our main result, where we show that when the objects are disks, of possibly differing radii, there is a (5+2√3)≈ 8.46 approximation algorithm. Additionally, for unit disks we give an O(n log k)+(k/ε)^O(k) time (1+ε)approximation to the optimal radius, that is, an FPTAS for constant k whose running time depends only linearly on n. Finally, we show that the one dimensional version of the problem, even when intersections are allowed, can be solved exactly in O(n log n) time.more » « less