The strong metric dimension of graphs and digraphs

Let G be a connected (di)graph. A vertex w is said to strongly resolve a pair u,v of vertices of G if there exists some shortest u-w path containing v or some shortest v-w path containing u. A set W of vertices is a strong resolving set for G if every pair of vertices of G is strongly resolved by some vertex of W. The smallest cardinality of a strong resolving set for G is called the strong dimension of G. It is shown that the problem of finding the strong dimension of a connected graph can be transformed to the problem of finding the vertex covering number of a graph. Moreover, it is shown that computing this invariant is NP-hard. Related invariants for directed graphs are defined and studied.     

Isometric embedding in products of complete graphs

An isometric (i.e., distance-preserving) embedding of a connected graph G into a cartesian product of complete graphs is equivalent to a labelling of each vertex of G by a string of symbols of fixed length such that the distance between two vertices is equal to the Hamming distance between the corresponding strings. Such a labelling could provide an addressing scheme for a communications network, since it enables a message to find a shortest path to its destination using only local information.We show that any two such embeddings of the same graph G are essentially the same, and give a polynomial-time algorithm which will find such an embedding if it exists. In addition we characterize the graphs which are isometrically embeddable in powers of K₃.     

On bounds for the cutting number of a graph

The cutting number of a vertex v of a finite graph G = (V,E) is a natural measure of the extent to which the removal of v disconnects the graph. Precisely, the cutting number c(v) of v is defined as the number of pairs of vertices {u,w} of G such that u,w ≠ v and every u-w path contains v. The cutting number c(G) of G is the maximum value of c(v) over all vertices in V. We provide exact bounds on the cutting number of G in terms of order and diameter of the graph.     

A characterization of the interval distance monotone graphs

A simple connected graph G is said to be interval distance monotone if the interval I(u,v) between any pair of vertices u and v in G induces a distance monotone graph. A?¨der and Aouchiche [Distance monotonicity and a new characterization of hypercubes, Discrete Math. 245 (2002) 55-62] proposed the following conjecture: a graph G is interval distance monotone if and only if each of its intervals is either isomorphic to a path or to a cycle or to a hypercube. In this paper we verify the conjecture.     

Steiner intervals and Steiner geodetic numbers in distance-hereditary graphs

A Steiner tree for a set S of vertices in a connected graph G is a connected subgraph of G with a smallest number of edges that contains S. The Steiner interval I(S) of S is the union of all the vertices of G that belong to some Steiner tree for S. If S={u,v}, then I(S)=I[u,v] is called the interval between u and v and consists of all vertices that lie on some shortest u-v path in G. The smallest cardinality of a set S of vertices such that ?_u,v∈SI[u,v]=V(G) is called the geodetic number and is denoted by g(G). The smallest cardinality of a set S of vertices of G such that I(S)=V(G) is called the Steiner geodetic number of G and is denoted by sg(G). We show that for distance-hereditary graphs g(G)?sg(G) but that g(G)/sg(G) can be arbitrarily large if G is not distance hereditary. An efficient algorithm for finding the Steiner interval for a set of vertices in a distance-hereditary graph is described and it is shown how contour vertices can be used in developing an efficient algorithm for finding the Steiner geodetic number of a distance-hereditary graph.     

The Cauchy problem for electromagnetic wave propagation in globally perturbed nonselfadjoint media

Let G be a subset of a locally convex separated topological vector space E with int(G) ≠ Ø, cl(G) convex and quasi-complete. Let f: cl(G) → E be a continuous condensing multifunction with compact and convex values and with a bounded range. It is shown that for each w? int(G), there exists a u = u(w) ??(cl(G)) such that p(f(u) ? u) = inf{p(x ? y): x?f(u), y? cl(G)}, where p is the Minkowski's functional of the set (cl(G) ? w). Several fixed point results are obtained as a consequence of this result.     

Distance-hereditary graphs and signpost systems

An ordered pair (U,R) is called a signpost system if U is a finite nonempty set, R⊆U×U×U, and the following axioms hold for all u,v,w∈U: (1) if (u,v,w)∈R, then (v,u,u)∈R; (2) if (u,v,w)∈R, then (v,u,w)∉R; (3) if u≠v, then there exists t∈U such that (u,t,v)∈R. (If F is a (finite) connected graph with vertex set U and distance function d, then U together with the set of all ordered triples (u,v,w) of vertices in F such that d(u,v)=1 and d(v,w)=d(u,w)−1 is an example of a signpost system). If (U,R) is a signpost system and G is a graph, then G is called the underlying graph of (U,R) if V(G)=U and xy∈E(G) if and only if (x,y,y)∈R (for all x,y∈U). It is possible to say that a signpost system shows a way how to travel in its underlying graph. The following result is proved: Let (U,R) be a signpost system and let G denote the underlying graph of (U,R). Then G is connected and every induced path in G is a geodesic in G if and only if (U,R) satisfies axioms (4)-(8) stated in this paper; note that axioms (4)-(8)-similarly as axioms (1)-(3)-can be formulated in the language of the first-order logic.     

Graphs with 1-Hamiltonian-connected cubes

The cube G³ of a connected graph G is that graph having the same vertex set as G and in which two distinct vertices are adjacent if and only if their distance in G is at most three. A Hamiltonian-connected graph has the property that every two distinct vertices are joined by a Hamiltonian path. A graph G is 1-Hamiltonian-connected if, for every vertex w of G, the graphs G and G?w are Hamiltonian-connected. A characterization of graphs whose cubes are 1-Hamiltonian-connected is presented.     

Optimal embeddings of odd ladders into a hypercube

An embedding of a graph G into a hypercube of dimension k is called optimal if the number of vertices of G is greater than 2^k−1. A ladder is a special graph in which two paths of the same length are connected in such a way that each vertex of the first one is connected by a path – called a rung – to its corresponding vertex in the second one. We construct an optimal embedding for every ladder with rungs of odd sizes greater than 6 into a dense set of a hypercube.     

Diameter-essential edges in a graph

The eccentricity e(v) of v is the distance to a farthest vertex from v. The diameter diam(G) is the maximum eccentricity among the vertices of G. The contraction of edge e=uv in G consists of removing e and identifying u and v as a single new vertex w, where w is adjacent to any vertex that at least one of u or v were adjacent to. The graph resulting from contracting edge e is denoted G/e. An edge e is diameter-essential if diam(G/e)<diam(G). Let c(G) denote the number of diameter-essential edges in graph G. In this paper, we study existence and extremal problems for c(G); determine bounds on c(G) in terms of diameter and order; and obtain characterizations of graphs achieving extreme values of c(G).     

Computing finest mincut partitions of a graph and application to routing problems

Let G=(V,E,w) be an n-vertex graph with edge weights w>0. We propose an algorithm computing all partitions of V into mincuts of G such that the mincuts in the partitions cannot be partitioned further into mincuts. There are O(n) such finest mincut partitions. A mincut is a non-empty proper subset of V such that the total weight of edges with exactly one end in the subset is minimal. The proposed algorithm exploits the cactus representation of mincuts and has the same time complexity as cactus construction. An application to the exact solution of the general routing problem is described.     

A Poset-based Approach to Embedding Median Graphs in Hypercubes and Lattices

A median graph G is a graph where, for any three vertices u, v and w, there is a unique node that lies on a shortest path from u to v, from u to w, and from v to w. While not obvious from the definition, median graphs are partial cubes; that is, they can be isometrically embedded in hypercubes and, consequently, in integer lattices. The isometric and lattice dimensions of G, denoted as dim _I (G) and dim _Z (G), are the smallest integers k and r so that G can be isometrically embedded in the k-dimensional hypercube and the r-dimensional lattice respectively. Motivated by recent results on the cover graphs of distributive lattices, we study these parameters through median semilattices, a class of ordered structures related to median graphs. We show that not only does this approach provide new combinatorial characterizations for dim _I (G) and dim _Z (G), they also have nice algorithmic consequences. Assume G has n vertices and m edges. We prove that dim _I (G) can be computed in O(n + m) time, and an isometric embedding of G on a hypercube with dimension dim _I (G) can be constructed in O(n × dim _I (G)) time. The algorithms are extremely simple and the running times are optimal. We also show that dim _Z (G) can be computed and an isometric embedding of G on a lattice with dimension dim _Z (G) can be constructed in O( n ×dim_I(G) + dim_I(G)^2.5)O( n \times dim_I(G) + dim_I(G)^{2.5}) time by using an existing algorithm of Eppstein’s that performs the same tasks for partial cubes. We are able to speed up his algorithm by using our framework to provide a new “interpretation” to the algorithm. In particular, we note that its main part is essentially a generalization of Fulkerson’s method for finding a smallest-sized chain decomposition of a poset.     

Geodesic-pancyclic graphs

A shortest path connecting two vertices u and v is called a u-v geodesic. The distance between u and v in a graph G, denoted by d_G(u,v), is the number of edges in a u-v geodesic. A graph G with n vertices is panconnected if, for each pair of vertices u,v∈V(G) and for each integer k with d_G(u,v)?k?n-1, there is a path of length k in G that connects u and v. A graph G with n vertices is geodesic-pancyclic if, for each pair of vertices u,v∈V(G), every u-v geodesic lies on every cycle of length k satisfying max{2d_G(u,v),3}?k?n. In this paper, we study sufficient conditions of geodesic-pancyclic graphs. In particular, we show that most of the known sufficient conditions of panconnected graphs can be applied to geodesic-pancyclic graphs.     

A Sharp Bound for the Marginal Appendage Number

For a connected graph G, the distance d(u, v) between two vertices u and v is the length of a shortest u − v path in G and the distance d(v) of a vertex v is the sum of the distances between v and all vertices of G. The margin, μ (G), is the subgraph induced by vertices of G having the maximum distance. It is known that every graph is isomorphic to the margin of some graph H. For a graph G, the marginal appendage number is defined as min{p(H) − p(G) ∣ μ(H) = G}. In this paper it is shown that Δ (G) + 2 is a sharp bound for the marginal appendage number.     

The asymptotic distribution of weighted empirical distribution functions

Let G_n denote the empirical distribution based on n independent uniform (0, 1) random variables. The asymptotic distribution of the supremum of weighted discrepancies between G_n(u) and u of the forms 6w_v(u)D_n(u)6 and 6w_v(G_n(u))D_n(u)6, where D_n(u) = G_n(u)?u, w_v(u) = (u(1?u))^?1+v and 0 ? v < $\text{1}\text{2}$ is obtained. Goodness-of-fit tests based on these statistics are shown to be asymptotically sensitive only in the extreme tails of a distribution, which is exactly where such statistics that use a weight function w_v with $\text{1}\text{2}$ ? v ? 1 are insensitive. For this reason weighted discrepancies which use the weight function w_v with 0 ? v < $\text{1}\text{2}$ are potentially applicable in the construction of confidence contours for the extreme tails of a distribution.     

The induced path function, monotonicity and betweenness

The geodesic interval function I of a connected graph allows an axiomatic characterization involving axioms on the function only, without any reference to distance, as was shown by Nebeský [20]. Surprisingly, Nebeský [23] showed that, if no further restrictions are imposed, the induced path function J of a connected graph G does not allow such an axiomatic characterization. Here J(u,v) consists of the set of vertices lying on the induced paths between u and v. This function is a special instance of a transit function. In this paper we address the question what kind of restrictions could be imposed to obtain axiomatic characterizations of J. The function J satisfies betweenness if w∈J(u,v), with w≠u, implies u∉J(w,v) and x∈J(u,v) implies J(u,x)⊆J(u,v). It is monotone if x,y∈J(u,v) implies J(x,y)⊆J(u,v). In the case where we restrict ourselves to functions J that satisfy betweenness, or monotonicity, we are able to provide such axiomatic characterizations of J by transit axioms only. The graphs involved can all be characterized by forbidden subgraphs.     

Minimal rankings and the arank number of a path

Given a graph G, a function f:V(G)→{1,2,…,k} is a k-ranking of G if f(u)=f(v) implies every u-v path contains a vertex w such that f(w)>f(u). A k-ranking is minimal if the reduction of any label greater than 1 violates the described ranking property. The arank number of a graph, denoted ψ_r(G), is the largest k such that G has a minimal k-ranking. We present new results involving minimal k-rankings of paths. In particular, we determine ψ_r(P_n), a problem posed by Laskar and Pillone in 2000.     

The Chartrand-Schuster conjecture: Graphs with unique distance trees are regular

Let G be a finite connected graph with no cut vertex. A distance tree T is a spanning tree of G which further satisfies the condition that for some vertex v, d_G(v, u) = d_T(v, u) for all u, where d_G(v, u) denotes the distance of u from v in the graph G. The conjecture that if all distance trees of G are isomorphic to each other then G is a regular graph, is settled affirmatively. The conjecture was made by Chartrand and Schuster.     

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 minimum metric dimension of honeycomb networks

A minimum metric basis is a minimum set W of vertices of a graph G(V,E) such that for every pair of vertices u and v of G, there exists a vertex wW with the condition that the length of a shortest path from u to w is different from the length of a shortest path from v to w. The honeycomb and hexagonal networks are popular mesh-derived parallel architectures. Using the duality of these networks we determine minimum metric bases for hexagonal and honeycomb networks.