Greedy approximation for the source location problem with vertex-connectivity requirements in undirected graphs

Let $G=(V,E)$ be a simple undirected graph with a set V of vertices and a set E of edges. Each vertex $v\in V$ has a demand $d(v)\in Z_{+}$, and a cost $c(v)\in R_{+}$, where $Z_{+}$ and $R_{+}$ denote the set of nonnegative integers and the set of nonnegative reals, respectively. The source location problem with vertex-connectivity requirements in a given graph G asks to find a set S of vertices minimizing ${\sum }_{v\in S}c(v)$ such that there are at least $d(v)$ pairwise vertex-disjoint paths from S to v for each vertex $v\in V?S$. It is known that the problem is not approximable within a ratio of $O(\ln {\sum }_{v\in V}d(v))$, unless NP has an $O(N^{\log \log N})$-time deterministic algorithm. Also, it is known that even if every vertex has a uniform cost and $d^1=4$ holds, then the problem is NP-hard, where $d^1=\max \{d(v)|v\in V\}$.In this paper, we consider the problem in the case where every vertex has uniform cost. We propose a simple greedy algorithm for providing a $\max \{d^1,2d^1?6\}$-approximate solution to the problem in $O(\min \{d^1,\sqrt{|V|}\}{d}^1{|V|}^2)$ time, while we also show that there exists an instance for which it provides no better than a $(d^1?1)$-approximate solution. Especially, in the case of $d^1?4$, we give a tight analysis to show that it achieves an approximation ratio of 3. We also show the APX-hardness of the problem even restricted to $d^1?4$.     

Augmenting Outerplanar Graphs to Meet Diameter Requirements

Given an undirected graph and an integer , we consider the problem of augmenting G by a minimum set of new edges so that the diameter becomes at most D. It is known that no constant factor approximation algorithms to this problem with an arbitrary graph G can be obtained unless , while the problem with only a few graph classes such as forests is approximable within a constant factor. In this article, we give the first constant factor approximation algorithm to the problem with an outerplanar graph G. We also show that if the target diameter D is even, then the case where G is a partial 2‐tree is also approximable within a constant.     

The source location problem with local 3-vertex-connectivity requirements

Let G=(V,E) be a simple undirected graph with a set V of vertices and a set E of edges. Each vertex v∈V has an integer valued demand d(v)?0. The source location problem with vertex-connectivity requirements in a given graph G asks to find a set S of vertices with the minimum cardinality such that there are at least d(v) vertex-disjoint paths between S and each vertex v∈V-S. In this paper, we show that the problem with d(v)?3, v∈V can be solved in linear time. Moreover, we show that in the case where d(v)?4 for some vertex v∈V, the problem is NP-hard.     

Minimum augmentation of local edge-connectivity between vertices and vertex subsets in undirected graphs

Given an undirected multigraph G=(V,E), a family W of sets W⊆V of vertices (areas), and a requirement function r:W→Z⁺ (where Z⁺ is the set of nonnegative integers), we consider the problem of augmenting G by the smallest number of new edges so that the resulting graph has at least r(W) edge-disjoint paths between v and W for every pair of a vertex v∈V and an area W∈W. So far this problem was shown to be NP-hard in the uniform case of r(W)=1 for each W∈W, and polynomially solvable in the uniform case of r(W)=r?2 for each W∈W. In this paper, we show that the problem can be solved in time, even if r(W)?2 holds for each W∈W, where n=|V|, m=|{{u,v}|(u,v)∈E}|, p=|W|, and r^*=max{r(W)∣W∈W}.     

Augmenting a graph of minimum degree 2 to have two disjoint total dominating sets

A total dominating set of a graph is a set of vertices such that every vertex is adjacent to a vertex in the set. We show that given a graph of order n with minimum degree at least 2, one can add at most edges such that the resulting graph has two disjoint total dominating sets, and this bound is best possible.     

Augmenting Edge-Connectivity over the Entire Range inÕ(nm) Time

For a given undirected graphG = (V, E, c_G) with edges weighted by nonnegative realsc_G:E → R ⁺ , let Λ_G(k) stand for the minimum amount of weights which needs to be added to makeG k-edge-connected, and letG*(k) be the resulting graph obtained fromG. This paper first shows that function Λ_Gover the entire rangek [0, +∞] can be computed inO(nm + n² log n) time, and then shows that allG*(k) in the entire range can be obtained fromO(n log n) weighted cycles, and such cycles can be computed inO(nm + n² log n) time, wherenandmare the numbers of vertices and edges, respectively.     

Splitting a planar graph of girth 5 into two forests with trees of small diameter

In 1985, Mihok and recently Axenovich, Ueckerdt, and Weiner asked about the minimum integer $g^1>3$ such that every planar graph with girth at least $g^1$ admits a 2-colouring of its vertices where the length of every monochromatic path is bounded from above by a constant. By results of Glebov and Zambalaeva and of Axenovich et al., it follows that $5\le g^1\le 6$. In this paper we establish that $g^1=5$. Moreover, we prove that every planar graph of girth at least 5 admits a 2-colouring of its vertices such that every monochromatic component is a tree of diameter at most 6. We also present the list version of our result.     

On the sizes of graphs and their powers: The undirected case

Let G be an undirected graph and G^r be its r-th power. We study different issues dealing with the number of edges in G and G^r. In particular, we answer the following question: given an integer r≥2 and all connected graphs G of order n such that G^r≠K_n, what is the minimum number of edges that are added when going from G to G^r, and which are the graphs achieving this bound?     

On the complexity of computing treelength

We resolve the computational complexity of determining the treelength of a graph, thereby solving an open problem of Dourisboure and Gavoille, who introduced this parameter, and asked to determine the complexity of recognizing graphs of a bounded treelength Dourisboure and Gavoille (2007) [6]. While recognizing graphs with treelength 1 is easily seen as equivalent to recognizing chordal graphs, which can be done in linear time, the computational complexity of recognizing graphs with treelength 2 was unknown until this result. We show that the problem of determining whether a given graph has a treelength at most k is NP-complete for every fixed k≥2, and use this result to show that treelength in weighted graphs is hard to approximate within a factor smaller than . Additionally, we show that treelength can be computed in time O^∗(1.7549ⁿ) by giving an exact exponential time algorithm for the Chordal Sandwich problem and showing how this algorithm can be used to compute the treelength of a graph.     

A faster 2-approximation algorithm for the minmax p-traveling salesmen problem on a tree

Given an edge-weighted tree T and an integer p1, the minmax p-traveling salesmen problem on a tree T asks to find p tours such that the union of the p tours covers all the vertices. The objective is to minimize the maximum of length of the p tours. It is known that the problem is NP-hard and has a (2−2/(p+1))-approximation algorithm which runs in O(p^p−1n^p−1) time for a tree with n vertices. In this paper, we consider an extension of the problem in which the set of vertices to be covered now can be chosen as a subset S of vertices and weights to process vertices in S are also introduced in the tour length. For the problem, we give an approximation algorithm that has the same performance guarantee, but runs in O((p−1)!·n) time.     

Customer order scheduling to minimize the number of late jobs

In the order scheduling problem, every job (order) consists of several tasks (product items), each of which will be processed on a dedicated machine. The completion time of a job is defined as the time at which all its tasks are finished. Minimizing the number of late jobs was known to be strongly NP-hard. In this note, we show that no FPTAS exists for the two-machine, common due date case, unless P = NP. We design a heuristic algorithm and analyze its performance ratio for the unweighted case. An LP-based approximation algorithm is presented for the general multicover problem. The algorithm can be applied to the weighted version of the order scheduling problem with a common due date.