L(p,q)-labeling of sparse graphs

Let p and q be positive integers. An L(p,q)-labeling of a graph G with a span s is a labeling of its vertices by integers between 0 and s such that adjacent vertices of G are labeled using colors at least p apart, and vertices having a common neighbor are labeled using colors at least q apart. We denote by λ _p,q (G) the least integer k such that G has an L(p,q)-labeling with span k. The maximum average degree of a graph G, denoted by $\operatorname {Mad}(G)$ , is the maximum among the average degrees of its subgraphs (i.e. $\operatorname {Mad}(G) = \max\{\frac{2|E(H)|}{|V(H)|} ; H \subseteq G \}$ ). We consider graphs G with $\operatorname {Mad}(G) < \frac{10}{3}$ , 3 and $\frac{14}{5}$ . These sets of graphs contain planar graphs with girth 5, 6 and 7 respectively. We prove in this paper that every graph G with maximum average degree m and maximum degree Δ has:

λ _p,q (G)≤(2q?1)Δ+6p+10q?8 if $m < \frac{10}{3}$ and p≥2q.

λ _p,q (G)≤(2q?1)Δ+4p+14q?9 if $m < \frac{10}{3}$ and 2q>p.

λ _p,q (G)≤(2q?1)Δ+4p+6q?5 if m<3.

λ _p,q (G)≤(2q?1)Δ+4p+4q?4 if $m < \frac{14}{5}$ .

We give also some refined bounds for specific values of p, q, or Δ. By the way we improve results of Lih and Wang (SIAM J. Discrete Math. 17(2):264–275, 2003).     

Semi-online scheduling for jobs with release times

In this paper we consider three semi-online scheduling problems for jobs with release times on m identical parallel machines. The worst case performance ratios of the LS algorithm are analyzed. The objective function is to minimize the maximum completion time of all machines, i.e. the makespan. If the job list has a non-decreasing release times, then $2-\frac{1}{m}$ is the tight bound of the worst case performance ratio of the LS algorithm. If the job list has non-increasing processing times, we show that $2-\frac{1}{2m}$ is an upper bound of the worst case performance ratio of the LS algorithm. Furthermore if the job list has non-decreasing release times and the job list has non-increasing processing times we prove that the LS algorithm has worst case performance ratio not greater than $\frac{3}{2} -\frac{1}{2m}$ .     

(p,q)-total labeling of complete graphs

Given a graph G and positive integers p,q with p≥q, the (p,q)-total number $\lambda_{p,q}^{T}(G)$ of G is the width of the smallest range of integers that suffices to label the vertices and the edges of G such that the labels of any two adjacent vertices are at least q apart, the labels of any two adjacent edges are at least q apart, and the difference between the labels of a vertex and its incident edges is at least p. Havet and Yu (Discrete Math 308:496–513, 2008) first introduced this problem and determined the exact value of $\lambda_{p,1}^{T}(K_{n})$ except for even n with p+5≤n≤6p ²?10p+4. Their proof for showing that $\lambda _{p,1}^{T}(K_{n})\leq n+2p-3$ for odd n has some mistakes. In this paper, we prove that if n is odd, then $\lambda_{p}^{T}(K_{n})\leq n+2p-3$ if p=2, p=3, or $4\lfloor\frac{p}{2}\rfloor+3\leq n\leq4p-1$ . And we extend some results that were given in Havet and Yu (Discrete Math 308:496–513, 2008). Beside these, we give a lower bound for $\lambda_{p,q}^{T}(K_{n})$ under the condition that q<p<2q.     

Online maximum directed cut

We investigate a natural online version of the well-known Maximum Directed Cut problem on DAGs. We propose a deterministic algorithm and show that it achieves a competitive ratio of $\frac{3\sqrt{3}}{2}\approx 2.5981$ . We then give a lower bound argument to show that no deterministic algorithm can achieve a ratio of $\frac{3\sqrt{3}}{2}-\epsilon$ for any ??>0 thus showing that our algorithm is essentially optimal. Then, we extend our technique to improve upon the analysis of an old result: we show that greedily derandomizing the trivial randomized algorithm for MaxDiCut in general graphs improves the competitive ratio from 4 to 3, and also provide a tight example.     

On sorting unsigned permutations by double-cut-and-joins

The problem of sorting unsigned permutations by double-cut-and-joins (SBD) arises when we perform the double-cut-and-join (DCJ) operations on pairs of unichromosomal genomes without the gene strandedness information. In this paper we show it is a NP-hard problem by reduction to an equivalent previously-known problem, called breakpoint graph decomposition (BGD), which calls for a largest collection of edge-disjoint alternating cycles in a breakpoint graph. To obtain a better approximation algorithm for the SBD problem, we made a suitable modification to Lin and Jiang’s algorithm which was initially proposed to approximate the BGD problem, and then carried out a rigorous performance analysis via fractional linear programming. The approximation ratio thus achieved for the SBD problem is $\frac{17}{12}+\epsilon \approx 1.4167 +\epsilon$ , for any positive ε.     

Directed Steiner trees with diffusion costs

Given a directed arc-weighted graph G with n nodes, a root r and k terminals, the directed steiner tree problem (DST) consists in finding a minimum-weight tree rooted at r and spanning all the terminals. If this problem has several applications in multicast routing in packet switching networks, the modeling is not adapted anymore in networks based upon the circuit switching principle in which some nodes, called non diffusing nodes, are unable to duplicate packets. We define a more general problem, namely the directed steiner tree with a limited number of diffusing nodes (DSTLD), that enables us to model multicast in a network containing at most d diffusing nodes. We show that DSTLD is XP with respect to d, and use this result to build a \(\left\lceil \frac{k-1}{d} \right\rceil \)-approximation algorithm for DST that is XP in d. We deduce from that result a strong inapproximability property. In particular, we prove that, under the assumption that NP \(\not \subseteq \) ZTIME \([n^{\log ^{O(1)}n}]\), there is no polynomial-time approximation algorithm for DSTLD with ratio \(\varOmega \left( \frac{k}{d}\right) \). We finally give an evaluation of performances of an exact algorithm dedicated to the case \(d \le 3\).     

Two-stage proportionate flexible flow shop to minimize the makespan

We consider a two-stage flexible flow shop problem with a single machine at one stage and m identical machines at the other stage, where the processing times of each job at both stages are identical. The objective is to minimize the makespan. We describe some optimality conditions and show that the problem is NP-hard when m is fixed. Finally, we present an approximation algorithm that has a worst-case performance ratio of $\frac{5}{4}$ for m=2 and $\frac{\sqrt{1+m^{2}}+1+m}{2m}$ for m≥3.     

Near optimal algorithms for online weighted bipartite matching in adversary model

Bipartite matching is an important problem in graph theory. With the prosperity of electronic commerce, such as online auction and AdWords allocation, bipartite matching problem has been extensively studied under online circumstances. In this work, we study the online weighted bipartite matching problem in adversary model, that is, there is a weighted bipartite graph \(G=(L,R,E)\) and the left side L is known as input, while the vertices in R come one by one in an order arranged by the adversary. When each vertex in R comes, its adjacent edges and relative weights are revealed. The algorithm should irreversibly decide whether to match this vertex to an unmatched neighbor in L with the objective to maximize the total weight of the obtained matching. When the weights are unbounded, the best algorithm can only achieve a competitive ratio \(\varTheta \left( \frac{1}{n}\right) \), where n is the number of vertices coming online. Thus, we mainly deal with two variants: the bounded weight problem in which all weights are in the range \([\alpha , \beta ]\), and the normalized summation problem in which each vertex in one side has the same total weights. We design algorithms for both variants with competitive ratio \(\varTheta \left( \max \left\{ \frac{1}{\log \frac{\beta }{\alpha }},\frac{1}{n}\right\} \right) \) and \(\varTheta \left( \frac{1}{\log n}\right) \) respectively. Furthermore, we show these two competitive ratios are tight by providing the corresponding hardness results.     

Efficient approximation algorithms for computing <Emphasis Type="Italic">k</Emphasis> disjoint constrained shortest paths

Let \(G=(V,\, E)\) be a given directed graph in which every edge e is associated with two nonnegative costs: a weight w(e) and a length l(e). For a pair of specified distinct vertices \(s,\, t\in V\), the k-(edge) disjoint constrained shortest path (kCSP) problem is to compute k (edge) disjoint paths between s and t, such that the total length of the paths is minimized and the weight is bounded by a given weight budget \(W\in \mathbb {R}_{0}^{+}\). The problem is known to be \({\mathcal {NP}}\)-hard, even when \(k=1\) (Garey and Johnson in Computers and intractability, 1979). Approximation algorithms with bifactor ratio \(\left( 1\,+\,\frac{1}{r},\, r\left( 1\,+\,\frac{2(\log r\,+\,1)}{r}\right) (1\,+\,\epsilon )\right) \) and \((1\,+\,\frac{1}{r},\,1\,+\,r)\) have been developed for \(k=2\) in Orda and Sprintson (IEEE INFOCOM, pp. 727–738, 2004) and Chao and Hong (IEICE Trans Inf Syst 90(2):465–472, 2007), respectively. For general k, an approximation algorithm with ratio \((1,\, O(\ln n))\) has been developed for a weaker version of kCSP, the k bi-constraint path problem which is to compute k disjoint st-paths satisfying a given length constraint and a weight constraint simultaneously (Guo et al. in COCOON, pp. 325–336, 2013). This paper first gives an approximation algorithm with bifactor ratio \((2,\,2)\) for kCSP using the LP-rounding technique. The algorithm is then improved by adopting a more sophisticated method to round edges. It is shown that for any solution output by the improved algorithm, there exists a real number \(0\le \alpha \le 2\) such that the weight and the length of the solution are bounded by \(\alpha \) times and \(2-\alpha \) times of that of an optimum solution, respectively. The key observation of the ratio proof is to show that the fractional edges, in a basic solution against the proposed linear relaxation of kCSP, exactly compose a graph in which the degree of every vertex is exactly two. At last, by a novel enhancement of the technique in Guo et al. (COCOON, pp. 325–336, 2013), the approximation ratio is further improved to \((1,\,\ln n)\).     

On judicious partitions of graphs

Let \(k, m\) be positive integers, let \(G\) be a graph with \(m\) edges, and let \(h(m)=\sqrt{2m+\frac{1}{4}}-\frac{1}{2}\). Bollobás and Scott asked whether \(G\) admits a \(k\)-partition \(V_{1}, V_{2}, \ldots , V_{k}\) such that \(\max _{1\le i\le k} \{e(V_{i})\}\le \frac{m}{k^2}+\frac{k-1}{2k^2}h(m)\) and \(e(V_1, \ldots , V_k)\ge {k-1\over k} m +{k-1\over 2k}h(m) -\frac{(k-2)^{2}}{8k}\). In this paper, we present a positive answer to this problem on the graphs with large number of edges and small number of vertices with degrees being multiples of \(k\). Particularly, if \(d\) is not a multiple of \(k\) and \(G\) is \(d\)-regular with \(m\ge {9\over 128}k^4(k-2)^2\), then \(G\) admits a \(k\)-partition as desired. We also improve an earlier result by showing that \(G\) admits a partition \(V_{1}, V_{2}, \ldots , V_{k}\) such that \(e(V_{1},V_{2},\ldots ,V_{k})\ge \frac{k-1}{k}m+\frac{k-1}{2k}h(m)-\frac{(k-2)^{2}}{2(k-1)}\) and \(\max _{1\le i\le k}\{e(V_{i})\}\le \frac{m}{k^{2}}+\frac{k-1}{2k^{2}}h(m)\).     

Paired-domination number of claw-free odd-regular graphs

A paired-dominating set of a graph G is a dominating set of vertices whose induced subgraph has a perfect matching, while the paired-domination number is the minimum cardinality of a paired-dominating set in the graph, denoted by \(\gamma _{pr}(G)\). Let G be a connected \(\{K_{1,3}, K_{4}-e\}\)-free cubic graph of order n. We show that \(\gamma _{pr}(G)\le \frac{10n+6}{27}\) if G is \(C_{4}\)-free and that \(\gamma _{pr}(G)\le \frac{n}{3}+\frac{n+6}{9(\lceil \frac{3}{4}(g_o+1)\rceil +1)}\) if G is \(\{C_{4}, C_{6}, C_{10}, \ldots , C_{2g_o}\}\)-free for an odd integer \(g_o\ge 3\); the extremal graphs are characterized; we also show that if G is a 2 -connected, \(\gamma _{pr}(G) = \frac{n}{3} \). Furthermore, if G is a connected \((2k+1)\)-regular \(\{K_{1,3}, K_4-e\}\)-free graph of order n, then \(\gamma _{pr}(G)\le \frac{n}{k+1} \), with equality if and only if \(G=L(F)\), where \(F\cong K_{1, 2k+2}\), or k is even and \(F\cong K_{k+1,k+2}\).     

The hamiltonian numbers in digraphs

In the paper, we study the hamiltonian numbers in digraphs. A hamiltonian walk of a digraph D is a closed spanning directed walk with minimum length in D. The length of a hamiltonian walk of a digraph D is called the hamiltonian number of D, denoted h(D). We prove that if a digraph D of order n is strongly connected, then $n\leq h(D)\leq\lfloor\frac{(n+1)^{2}}{4} \rfloor$ , and hence characterize the strongly connected digraphs of order n with hamiltonian number $\lfloor\frac{(n+1)^{2}}{4} \rfloor$ . In addition, we show that for each k with $4\leq n\leq k\leq\lfloor \frac{(n+1)^{2}}{4} \rfloor$ , there exists a digraph with order n and hamiltonian number k. Furthermore, we also study the hamiltonian spectra of graphs.     

A primal–dual online algorithm for the <Emphasis Type="Italic">k</Emphasis>-server problem on weighted HSTs

In this paper, we show that there is a \(\frac{5}{2}\ell \cdot \ln (1+k)\)-competitive randomized algorithm for the k-sever problem on weighted Hierarchically Separated Trees (HSTs) with depth \(\ell \) when \(n=k+1\) where n is the number of points in the metric space, which improved previous best competitive ratio \(12 \ell \ln (1+4\ell (1+k))\) by Bansal et al. (FOCS, pp 267–276, 2011).     

Critical edges/nodes for the minimum spanning tree problem: complexity and approximation

In this paper, we study the complexity and the approximation of the k most vital edges (nodes) and min edge (node) blocker versions for the minimum spanning tree problem (MST). We show that the k most vital edges MST problem is NP-hard even for complete graphs with weights 0 or 1 and 3-approximable for graphs with weights 0 or 1. We also prove that the k most vital nodes MST problem is not approximable within a factor n ^1?? , for any ?>0, unless NP=ZPP, even for complete graphs of order n with weights 0 or 1. Furthermore, we show that the min edge blocker MST problem is NP-hard even for complete graphs with weights 0 or 1 and that the min node blocker MST problem is NP-hard to approximate within a factor 1.36 even for graphs with weights 0 or 1.     

On the most imbalanced orientation of a graph

We study the problem of orienting the edges of a graph such that the minimum over all the vertices of the absolute difference between the outdegree and the indegree of a vertex is maximized. We call this minimum the imbalance of the orientation, i.e. the higher it gets, the more imbalanced the orientation is. The studied problem is denoted by \({{\mathrm{\textsc {MaxIm}}}}\). We first characterize graphs for which the optimal objective value of \({{\mathrm{\textsc {MaxIm}}}}\) is zero. Next we show that \({{\mathrm{\textsc {MaxIm}}}}\) is generally NP-hard and cannot be approximated within a ratio of \(\frac{1}{2}+\varepsilon \) for any constant \(\varepsilon >0\) in polynomial time unless \(\texttt {P}=\texttt {NP}\) even if the minimum degree of the graph \(\delta \) equals 2. Then we describe a polynomial-time approximation algorithm whose ratio is almost equal to \(\frac{1}{2}\). An exact polynomial-time algorithm is also derived for cacti. Finally, two mixed integer linear programming formulations are presented. Several valid inequalities are exhibited with the related separation algorithms. The performance of the strengthened formulations is assessed through several numerical experiments.     

Nordhaus–Gaddum type result for the matching number of a graph

For a graph G, \(\alpha '(G)\) is the matching number of G. Let \(k\ge 2\) be an integer, \(K_{n}\) be the complete graph of order n. Assume that \(G_{1}, G_{2}, \ldots , G_{k}\) is a k-decomposition of \(K_{n}\). In this paper, we show that (1)

$$\begin{aligned} \left\lfloor \frac{n}{2}\right\rfloor \le \sum _{i=1}^{k} \alpha '(G_{i})\le k\left\lfloor \frac{n}{2}\right\rfloor . \end{aligned}$$

(2) If each \(G_{i}\) is non-empty for \(i = 1, \ldots , k\), then for \(n\ge 6k\),

$$\begin{aligned} \sum _{i=1}^{k} \alpha '(G_{i})\ge \left\lfloor \frac{n+k-1}{2}\right\rfloor . \end{aligned}$$

(3) If \(G_{i}\) has no isolated vertices for \(i = 1, \ldots , k\), then for \(n\ge 8k\),

$$\begin{aligned} \sum _{i=1}^{k} \alpha '(G_{i})\ge \left\lfloor \frac{n}{2}\right\rfloor +k. \end{aligned}$$

The bounds in (1), (2) and (3) are sharp. (4) When \(k= 2\), we characterize all the extremal graphs which attain the lower bounds in (1), (2) and (3), respectively.

     

Online covering salesman problem

Given a graph \(G=(V,E,D,W)\), the generalized covering salesman problem (CSP) is to find a shortest tour in G such that each vertex \(i\in D\) is either on the tour or within a predetermined distance L to an arbitrary vertex \(j\in W\) on the tour, where \(D\subset V\),\(W\subset V\). In this paper, we propose the online CSP, where the salesman will encounter at most k blocked edges during the traversal. The edge blockages are real-time, meaning that the salesman knows about a blocked edge when it occurs. We present a lower bound \(\frac{1}{1 + (k + 2)L}k+1\) and a CoverTreeTraversal algorithm for online CSP which is proved to be \(k+\alpha \)-competitive, where \(\alpha =0.5+\frac{(4k+2)L}{OPT}+2\gamma \rho \), \(\gamma \) is the approximation ratio for Steiner tree problem and \(\rho \) is the maximal number of locations that a customer can be served. When \(\frac{L}{\texttt {OPT}}\rightarrow 0\), our algorithm is near optimal. The problem is also extended to the version with service cost, and similar results are derived.     

An FPTAS for generalized absolute 1-center problem in vertex-weighted graphs

Given a vertex-weighted undirected connected graph \(G = (V, E, \ell , \rho )\), where each edge \(e \in E\) has a length \(\ell (e) > 0\) and each vertex \(v \in V\) has a weight \(\rho (v) > 0\), a subset \(T \subseteq V\) of vertices and a set S containing all the points on edges in a subset \(E' \subseteq E\) of edges, the generalized absolute 1-center problem (GA1CP), an extension of the classic vertex-weighted absolute 1-center problem (A1CP), asks to find a point from S such that the longest weighted shortest path distance in G from it to T is minimized. This paper presents a simple FPTAS for GA1CP by traversing the edges in \(E'\) using a positive real number as step size. The FPTAS takes \(O( |E| |V| + |V|^2 \log \log |V| + \frac{1}{\epsilon } |E'| |T| {\mathcal {R}})\) time, where \({\mathcal {R}}\) is an input parameter size of the problem instance, for any given \(\epsilon > 0\). For instances with a small input parameter size \({\mathcal {R}}\), applying the FPTAS with \(\epsilon = \Theta (1)\) to the classic vertex-weighted A1CP can produce a \((1 + \Theta (1))\)-approximation in at most O(|E| |V|) time when the distance matrix is known and \(O(|E| |V| + |V|^2 \log \log |V|)\) time when the distance matrix is unknown, which are smaller than Kariv and Hakimi’s \(O(|E| |V| \log |V|)\)-time algorithm and \(O(|E| |V| \log |V| + |V|^3)\)-time algorithm, respectively.     

Improved upper bound for the degenerate and star chromatic numbers of graphs

Let \(G=G(V,E)\) be a graph. A proper coloring of G is a function \(f:V\rightarrow N\) such that \(f(x)\ne f(y)\) for every edge \(xy\in E\). A proper coloring of a graph G such that for every \(k\ge 1\), the union of any k color classes induces a \((k-1)\)-degenerate subgraph is called a degenerate coloring; a proper coloring of a graph with no two-colored \(P_{4}\) is called a star coloring. If a coloring is both degenerate and star, then we call it a degenerate star coloring of graph. The corresponding chromatic number is denoted as \(\chi _{sd}(G)\). In this paper, we employ entropy compression method to obtain a new upper bound \(\chi _{sd}(G)\le \lceil \frac{19}{6}\Delta ^{\frac{3}{2}}+5\Delta \rceil \) for general graph G.     

Cost sharing and strategyproof mechanisms for set cover games

We develop for set cover games several general cost-sharing methods that are approximately budget-balanced, in the core, and/or group-strategyproof. We first study the cost sharing for a single set cover game, which does not have a budget-balanced mechanism in the core. We show that there is no cost allocation method that can always recover more than $\frac{1}{\ln n}$ of the total cost and in the core. Here n is the number of all players to be served. We give a cost allocation method that always recovers $\frac{1}{\ln d_{\mathit{max}}}$ of the total cost, where d _max is the maximum size of all sets. We then study the cost allocation scheme for all induced subgames. It is known that no cost sharing scheme can always recover more than $\frac{1}{n}$ of the total cost for every subset of players. We give an efficient cost sharing scheme that always recovers at least $\frac{1}{2n}$ of the total cost for every subset of players and furthermore, our scheme is cross-monotone. When the elements to be covered are selfish agents with privately known valuations, we present a strategyproof charging mechanism, under the assumption that all sets are simple sets; further, the total cost of the set cover is no more than ln?d _max times that of an optimal solution. When the sets are selfish agents with privately known costs, we present a strategyproof payment mechanism to them. We also show how to fairly share the payments to all sets among the elements.