Usually several neighborhood structures may be explored within a single local search algorithm. The simplest way is to define a single neighborhood as a unio...

In the present paper, we are interested in bounding differences between graph invariants as well as in characterizing the corresponding extremal graphs. This...

Le laplacien sans signe des distances d'un graphe connexe \(G\) est défini par \(\mathcal{D}^\mathcal{Q} = Diag(Tr) + \mathcal{D}\), où \(\mathcal{D}\)...

La proximité \(\pi\) et l'éloignement \(\rho\) sont respectivement le minimum et le maximum, pour les sommets d'un graphe connexe, de la distance moyenne...

Finding communities in complex networks is a topic of much current research and has applications in many domains. On the one hand, criteria for doing so hav...

The analysis of networks and in particular the identification of communities, or clusters, is a topic of active research with application arising in many dom...

In 1971, Graham and Pollack established a relationship between the number of negative eigenvalues of the distance matrix and the addressing problem in data c...

La recherche à voisinages variables (RVV), ou <i>Variable Neighborhood Search (VNS)</i> en anglais est une métaheuristique dont l'invention est due à Nenad ...

Variable neighborhood search (VNS) is a meta-heuristic for solving optimization problems, whose basic idea is a systematic change of neighborhood structure...

The distance Laplacian of a connected graph G is defined by L = Diag(Tr) - D, where D is the distance matrix of G , and Diag(Tr) is the diagonal m...

In the present paper, we are interested in studying mathematical properties of the Balaban index of connected graphs. We present a discussion on and refuta...

Introduced during the late nineties of the last century, Variable Neighborhood Search (VNS) was first designed for solving specific problems in combinatorial...

We introduce a Laplacian and a signless Laplacian for the distance matrix of a connected graph, called the <i>distance Laplacian</i> and <i>distance signless...

We derive conditions on the functions \(\varphi\), \(\rho\), \(v\) and \(w\) such that the 0-1 fractional programming problem`(\max\limits_{x\in {0...

Application of the dispersion models in order to address the cannibalization phenomenon within franchised chains is a new approach. In this work we have deve...

Community detection in networks has been studied extensively in the last decade. Many criteria, expressing the quality of the partitions obtained, as well ...

Sequential clustering aims at determining homogeneous and/or well-separated clusters within a given set of entities, one at a time, until no more such clus...

Reduced RLT constraints are a special class of Reformulation-Linearization Technique (RLT) constraints. They apply to nonconvex (both continuous and mixed-...

Given a set of entities, cluster analysis aims at finding subsets, also called clusters or communities or modules, entities of which are homogeneous and well...

Finding clusters, or communities, in a graph, or network is a very important problem which arises in many domains. Several models were proposed for its solu...