Optimal broadcast domination in polynomial time

Broadcast domination was introduced by Erwin in 2002, and it is a variant of the standard dominating set problem, such that different vertices can be assigned different domination powers. Broadcast domination assigns an integer power f(v)?0 to each vertex v of a given graph, such that every vertex of the graph is within distance f(v) from some vertex v having f(v)?1. The optimal broadcast domination problem seeks to minimize the sum of the powers assigned to the vertices of the graph. Since the presentation of this problem its computational complexity has been open, and the general belief has been that it might be NP-hard. In this paper, we show that optimal broadcast domination is actually in P, and we give a polynomial time algorithm for solving the problem on arbitrary graphs, using a non-standard approach.     

Rainbow domination on trees

This paper studies a variation of domination in graphs called rainbow domination. For a positive integer k, a k-rainbow dominating function of a graph G is a function f from V(G) to the set of all subsets of {1,2,…,k} such that for any vertex v with f(v)=0? we have ∪_u∈NG(v)f(u)={1,2,…,k}. The 1-rainbow domination is the same as the ordinary domination. The k-rainbow domination problem is to determine the k-rainbow domination number of a graph G, that is the minimum value of ∑_v∈V(G)|f(v)| where f runs over all k-rainbow dominating functions of G. In this paper, we prove that the k-rainbow domination problem is NP-complete even when restricted to chordal graphs or bipartite graphs. We then give a linear-time algorithm for the k-rainbow domination problem on trees. For a given tree T, we also determine the smallest k such that .     

Models and methods for standardization problems

When designing an information system, the so-called “Standardization Problem” (SP) arises. The (basic) problem can be described by means of a graph with n nodes and e edges. The nodes represent system elements which have to share information with other nodes. For each system element i, it is possible to introduce a (new) standard, causing fixed costs. In turn, information exchange becomes more efficient if sender i and receiver j introduce the (same) standard, which results in lower exchange costs. The task is to decide for any combination of a system element i and a standard k if k should be introduced in i, so that the sum of setup and exchange costs is minimized. Models and (exact) solution methods are presented for the basic SP as well as for a generalization. Complexity issues are also discussed.     

Path Ramsey numbers in multicolorings

In this paper we consider the general Ramsey number problem for paths when the complete graph is colored with k colors. Specifically, given paths P_i1, P_i2,…, P_ik with i₁, i₂,…, i_k vertices, we determine for certain i_j (1 ≤ j ≤ k) the smallest positive integer n such that a k coloring of the complete graph K_n contains, for some l, a P_il in the lth color. For k = 3, given i₂, i₃, the problem is solved for all but a finite number of values of i₁. The procedure used in the proof uses an improvement of an extremal theorem for paths by P. Erdös and T. Gallai.     

The complexity of generalized clique packing

The K_i - j packing problem P_{i, j} is defined as follows: Given a graph G and integer k does there exist a set of at least kK_i's in G such that no two of these K_i's intersect in more than j nodes. This problem includes such problems as matching, vertex partitioning into complete subgraphs and edge partitioning into complete subgraphs. In this paper it is shown thhat for i ? 3 and 0?j?i ?2 the P_{i, j} problems is NP-complete. Furthermore, the problems remains NP-complete for i?3 and 1?j?i ?2 for chordal graphs.     

Flow trees for vertex-capacitated networks

Given a graph G=(V,E) with a cost function , we want to represent all possible min-cut values between pairs of vertices i and j. We consider also the special case with an additive cost c where there are vertex capacities c(v)?0∀v∈V, and for a subset S⊆V, c(S)=∑_v∈Sc(v). We consider two variants of cuts: in the first one, separation, {i} and {j} are feasible cuts that disconnect i and j. In the second variant, vertex-cut, a cut-set that disconnects i from j does not include i or j. We consider both variants for undirected and directed graphs. We prove that there is a flow-tree for separations in undirected graphs. We also show that a compact representation does not exist for vertex-cuts in undirected graphs, even with additive costs. For directed graphs, a compact representation of the cut-values does not exist even with additive costs, for neither the separation nor the vertex-cut cases.     

Integer version of the multipath flow network synthesis problem

We consider the following integer multipath flow network synthesis problem. We are given two positive integers q, n, (1<q<n), and a non-negative, integer, symmetric, n×n matrix R, each non-diagonal element r_ij of which represents the minimum requirement of q-path flow value between nodes i and j in an undirected network on the node set N={1,2,…,n}. We want to construct a simple, undirected network G=[N,E] with integer edge capacities {u_e:e∈E} such that each of these flow requirements can be realized (one at a time) and the sum of all the edge capacities is minimum. We present an O(n³) combinatorial algorithm for the problem and we show that the problem has integer rounding property.     

New bounds for the broadcast domination number of a graph

A dominating broadcast on a graph G = (V, E) is a function f: V → {0, 1, ..., diam G} such that f(v) ≤ e(v) (the eccentricity of v) for all v ∈ V and such that each vertex is within distance f(v) from a vertex v with f(v) > 0. The cost of a broadcast f is σ(f) = Σ _v∈V f(v), and the broadcast number λ _b (G) is the minimum cost of a dominating broadcast. A set X ? V(G) is said to be irredundant if each x ∈ X dominates a vertex y that is not dominated by any other vertex in X; possibly y = x. The irredundance number ir (G) is the cardinality of a smallest maximal irredundant set of G. We prove the bound λ_b(G) ≤ 3 ir(G)/2 for any graph G and show that equality is possible for all even values of ir (G). We also consider broadcast domination as an integer programming problem, the dual of which provides a lower bound for λ_b.     

Acyclic colorings of graphs with bounded degree

A k-coloring (not necessarily proper) of vertices of a graph is called acyclic, if for every pair of distinct colors i and j the subgraph induced by the edges whose endpoints have colors i and j is acyclic. We consider some generalized acyclic k-colorings, namely, we require that each color class induces an acyclic or bounded degree graph. Mainly we focus on graphs with maximum degree 5. We prove that any such graph has an acyclic 5-coloring such that each color class induces an acyclic graph with maximum degree at most 4. We prove that the problem of deciding whether a graph G has an acyclic 2-coloring in which each color class induces a graph with maximum degree at most 3 is NP-complete, even for graphs with maximum degree 5. We also give a linear-time algorithm for an acyclic t-improper coloring of any graph with maximum degree d assuming that the number of colors is large enough.     

A combinatorial problem involving graphs and matrices

In this paper we discuss a combinatorial problem involving graphs and matrices. Our problem is a matrix analogue of the classical problem of finding a system of distinct representatives (transversal) of a family of sets and relates closely to an extremal problem involving 1-factors and a long standing conjecture in the dimension theory of partially ordered sets. For an integer n ?1, let n denote the n element set {1,2,3,…, n}. Then let A be a k×t matrix. We say that A satisfies property P(n, k) when the following condition is satisfied: For every k-taple (x₁,x₂,…,x_k?n^k there exist k distinct integers j₁,j₂,…,j_k so that x_i= a_ii for i= 1,2,…,k. The minimum value of t for which there exists a k × t matrix A satisfying property P(n,k) is denoted by f(n,k). For each k?1 and n sufficiently large, we give an explicit formula for f(n, k): for each n?1 and k sufficiently large, we use probabilistic methods to provide inequalities for f(n,k).     

On integral sum graphs

A graph G is said to be an integral sum graph if its nodes can be given a labeling f with distinct integers, so that for any two distinct nodes u and v of G, uv is an edge of G if and only if f(u)+f(v)=f(w) for some node w in G. A node of G is called a saturated node if it is adjacent to every other node of G. We show that any integral sum graph which is not K₃ has at most two saturated nodes. We determine the structure for all integral sum graphs with exactly two saturated nodes, and give an upper bound for the number of edges of a connected integral sum graph with no saturated nodes. We introduce a method of identification on constructing new connected integral sum graphs from given integral sum graphs with a saturated node. Moreover, we show that every graph is an induced subgraph of a connected integral sum graph. Miscellaneous related results are also presented.     

On Integral Sum Graphs

A graph G is said to be an integral sum graph if its nodes can be given a labeling f with distinct integers, so that for any two distinct nodes u and v of G, uv is an edge of G if and only if f(u)+f(v) = f(w) for some node w in G. A node of G is called a saturated node if it is adjacent to every other node of G. We show that any integral sum graph which is not K₃ has at most two saturated nodes. We determine the structure for all integral sum graphs with exactly two saturated nodes, and give an upper bound for the number of edges of a connected integral sum graph with no saturated nodes. We introduce a method of identification on constructing new connected integral sum graphs from given integral sum graphs with a saturated node. Moreover, we show that every graph is an induced subgraph of a connected integral sum graph. Miscellaneous relative results are also presented.     

Acyclic improper colouring of graphs with maximum degree 4

A k-colouring(not necessarily proper) of vertices of a graph is called acyclic, if for every pair of distinct colours i and j the subgraph induced by the edges whose endpoints have colours i and j is acyclic. We consider acyclic k-colourings such that each colour class induces a graph with a given(hereditary) property. In particular, we consider acyclic k-colourings in which each colour class induces a graph with maximum degree at most t, which are referred to as acyclic t-improper k-colourings. The acyclic t-improper chromatic number of a graph G is the smallest k for which there exists an acyclic t-improper k-colouring of G. We focus on acyclic colourings of graphs with maximum degree 4. We prove that 3 is an upper bound for the acyclic 3-improper chromatic number of this class of graphs. We also provide a non-trivial family of graphs with maximum degree4 whose acyclic 3-improper chromatic number is at most 2, namely, the graphs with maximum average degree at most 3. Finally, we prove that any graph G with Δ(G) 4 can be acyclically coloured with 4 colours in such a way that each colour class induces an acyclic graph with maximum degree at most 3.     

On minimum power connectivity problems

Given a (directed or undirected) graph with edge costs, the power of a node is the maximum cost of an edge leaving it, and the power of the graph is the sum of the powers of its nodes. Motivated by applications for wireless networks, we present polynomial and improved approximation algorithms, as well as inapproximability results, for some classic network design problems under the power minimization criteria. Our main result is for the problem of finding a min-power subgraph that contains k internally-disjoint vs-paths from every node v to a given node s: we give a polynomial algorithm for directed graphs and a logarithmic approximation algorithm for undirected graphs. In contrast, we will show that the corresponding edge-connectivity problems are unlikely to admit even a polylogarithmic approximation.     

Two Forbidden Subgraph Pairs for Hamiltonicity of 3-Connected Graphs

For integers i, j, k with ${i\geq j\geq k\geq 0}$ , let N _{i, j, k} be the graph obtained by identifying end vertices of three disjoint paths of lengths i, j, k to the vertices of a triangle. In this paper, we show that every 3-connected {K _1,3, N _{i, 7-i, 2}}-free graph is hamiltonian, where ${i \in \{4,5\}}$ . This result is sharp in the sense that no one of the numbers i, 7?i and 2 in N _{i, 7-i, 2} can be replaced by a larger number.     

On a binary distance model for the minimum linear arrangement problem

The minimum linear arrangement problem consists of finding an embedding of the nodes of a graph on the line such that the sum of the resulting edge lengths is minimized. The problem is among the classical NP-hard optimization problems and there has been extensive research on exact and approximative algorithms. In this paper, we introduce a new model based on binary variables d _ijk that are equal to 1 if nodes i and j have distance k in the ordering. We analyze this model and point to connections and differences to a model using integer distance variables. Based on computational experiments, we argue that our model is worth further theoretical and practical investigation and that is has potentials yet to be examined.     

A note on the minimum total coloring of planar graphs

Graph coloring is an important tool in the study of optimization,computer science,network design,e.g.,file transferring in a computer network,pattern matching,computation of Hessians matrix and so on.In this paper,we consider one important coloring,vertex coloring of a total graph,which is also called total coloring.We consider a planar graph G with maximum degree Δ(G)≥8,and proved that if G contains no adjacent i,j-cycles with two chords for some i,j∈{5,6,7},then G is total-(Δ+1)-colorable.     

Induced disjoint paths problem in a planar digraph

As an extension of the disjoint paths problem, we introduce a new problem which we call the induced disjoint paths problem. In this problem we are given a graph G and a collection of vertex pairs {(s₁,t₁),…,(s_k,t_k)}. The objective is to find k paths P₁,…,P_k such that P_i is a path from s_i to t_i and P_i and P_j have neither common vertices nor adjacent vertices for any distinct i,j.The induced disjoint paths problem has several variants depending on whether k is a fixed constant or a part of the input, whether the graph is directed or undirected, and whether the graph is planar or not. We investigate the computational complexity of several variants of the induced disjoint paths problem. We show that the induced disjoint paths problem is (i) solvable in polynomial time when k is fixed and G is a directed (or undirected) planar graph, (ii) NP-hard when k=2 and G is an acyclic directed graph, (iii) NP-hard when k=2 and G is an undirected general graph.As an application of our first result, we show that we can find in polynomial time certain structures called a “hole” and a “theta” in a planar graph.     

A weighted geometric regularity from order restricted statistical inference

In Euclideank-space, the cone of vectors x = (x ₁,x ₂,...,x _k ) satisfyingx ₁ ≤x ₂ ≤ ... ≤x _k and $\sum\nolimits_{j = 1}^k {x_j } = 0$ is generated by the vectorsv _j = (j ?k, ...,j ?k,j, ...,j) havingj ?k’s in its firstj coordinates andj’s for the remainingk ?j coordinates, for 1 ≤j <k. In this equal weights case, the average angle between v _i and v _j over all pairs (i, j) with 1 ≤i <j <k is known to be 60°. This paper generalizes the problem by considering arbitrary weights with permutations.     

Some topological properties of star graphs: The surface area and volume

The star graph, as an interesting network topology, has been extensively studied in the past. In this paper, we address some of the combinatorial properties of the star graph. In particular, we consider the problem of calculating the surface area and volume of the star graph, and thus answering an open problem previously posed in the literature. The surface area of a sphere with radius i in a graph is the number of nodes in the graph whose distance from a given node is exactly i. The volume of a sphere with radius i in a graph is the number of nodes within distance i from the given node. In this paper, we derive explicit expressions to calculate the surface area and volume in the star graph.