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Tight approximation algorithms for bichromatic graph diameter and related problems. (English) Zbl 07561540

Baier, Christel (ed.) et al., 46th international colloquium on automata, languages, and programming, ICALP 2019, Patras, Greece, July 9–12, 2019. Proceedings. Wadern: Schloss Dagstuhl – Leibniz-Zentrum für Informatik. LIPIcs – Leibniz Int. Proc. Inform. 132, Article 47, 15 p. (2019).
Summary: Some of the most fundamental and well-studied graph parameters are the Diameter (the largest shortest paths distance) and Radius (the smallest distance for which a “center” node can reach all other nodes). The natural and important \(ST\)-variant considers two subsets \(S\) and \(T\) of the vertex set and lets the \(ST\)-diameter be the maximum distance between a node in \(S\) and a node in \(T\), and the \(ST\)-radius be the minimum distance for a node of \(S\) to reach all nodes of \(T\). The bichromatic variant is the special case in which \(S\) and \(T\) partition the vertex set.
In this paper we present a comprehensive study of the approximability of \(ST\) and Bichromatic Diameter, Radius, and Eccentricities, and variants, in graphs with and without directions and weights. We give the first nontrivial approximation algorithms for most of these problems, including time/accuracy trade-off upper and lower bounds. We show that nearly all of our obtained bounds are tight under the Strong Exponential Time Hypothesis (SETH), or the related Hitting Set Hypothesis.
For instance, for Bichromatic Diameter in undirected weighted graphs with m edges, we present an \(\widetilde{O}(m^{3/2})\) time \(5/3\)-approximation algorithm, and show that under SETH, neither the running time, nor the approximation factor can be significantly improved while keeping the other unchanged.
For the entire collection see [Zbl 1414.68003].

MSC:

68Nxx Theory of software
68Qxx Theory of computing

References:

[1] If the k-OV instance has a solution, then there exists a pair of vertices u ∈ S and v ∈ T such that d(u, v) ≥ 4k − 3.
[2] Proof. Construction of the graph. We begin with the k-OV-graph from Theorem 8. Additionally, we add k − 1 new layers of vertices L k+1 , . . . , L 2k−1 , where each new layer contains n k−1 vertices and is connected to the previous layer by a matching. That is, each new layer contains one vertex for every tuple (a 1 , . . . , a k−1 ) where a i ∈ W i for all i, and each (a 1 , . . . , a k−1 ) ∈ L j is connected to its counterpart (a 1 , . . . , a k−1 ) ∈ L j−1 by an edge, for all j. We let S = L 0 and we let T contain the rest of the vertices in the graph.
[3] Correctness of the construction. Case 1: The k-OV instance has no solution. By property 3 of Theorem 8 for all u ∈ S and v ∈ L k , d(u, v) = k. Then, since L k , . . . , L 2k−1 form a series of matchings, for all u ∈ S and v ∈ L k+1 ∪ • • • ∪ L 2k−1 , d(u, v) ≤ 2k − 1. Furthermore, property 5 of Theorem 8 implies that for all u ∈ S and v ∈ L 1 ∪ • • • ∪ L k−1 , d(u, v) ≤ 2k − 1. Thus, we have shown that for all u ∈ S and v ∈ T we have d(u, v) ≤ 2k − 1.
[4] Case 2: The k-OV instance has a solution. Let (a 0 , a 1 , . . . , a k−1 ) be a solution to the k-OV instance where a i ∈ W i for all i. We claim that d((a 0 , . . . , a k−2 ) ∈ S, (a 1 , . . . , a k−1 ) ∈ L 2k−1 )) ≥ 4k − 3. Since L k , . . . , L 2k−1 form a series of matchings, every path from (a 0 , . . . , a k−2 ) ∈ S to (a 1 , . . . , a k−1 ) ∈ L 2k−1 contains the vertex (a 1 , . . . , a k−1 ) ∈ L k . By property 4 of Theorem 8, d((a 0 , . . . , a k−2 ) ∈ S, (a 1 , . . . , a k−1 ) ∈ L k ) ≥ 3k − 2. Thus, d((a 0 , . . . , a k−2 ) ∈ S, (a 1 , . . . , a k−1 ) ∈ L 2k−1 )) ≥ 4k − 3.
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