Finding Paths in Graphs Avoiding Forbidden Transitions;

Let v be a vertex of a graph G; a transition graph T(v) of v is a graph whose vertices are the edges incident with v. We consider graphs G with prescribed transition systems T={T(v) | vV(G)}. A path P in G is called T-compatible, if each pair uv,vw of consecutive edges of P form an edge in T(v). Let be a given class of graphs (closed under isomorphism). We study the computational complexity of finding T-compatible paths between two given vertices of a graph for a specified transition system . Our main result is that a dichotomy holds (subject to the assumption P≠NP). That is, for a considered class , the problem is either (1) NP-complete, or (2) it can be solved in linear time. We give a criterion—based on vertex induced subgraphs—which decides whether (1) or (2) holds for any given class

Autour de la connexité dans les graphes avec conflits

We will look at graphs with conflicts (conflict is a pair of edges can not simultaneously be part of the same subgraph), in which we will study different types of problems related to the existence of subgraphs without conflict. The nature of the problems is both combinatorial and algorithmic. Our guideline is the notion of connectivity. We will see several results, simple without conflict, are no longer when adding conflicts. We will present exact algorithms (not polynomial), \mathcal{N P}-completeness results and sufficient conditions ensuring the existence of certain objects (spanning tree, path and Hamiltonian cycle) without conflict.Nous nous intéresserons aux graphes avec conflits (un conflit est une paire d’arêtes ne pouvant pas simultanément faire partie d’un même sous-graphe), dans lesquels nous étudierons différents types de problèmes liés à l’existence de sous-graphes sans conflit, de nature aussi bien algorithmique que combinatoire, notre ligne directrice étant la notion de connectivité. Nous verrons que plusieurs résultats, simples sans conflit, ne le sont plus lors de l’ajout de conflits. Nous présenterons : des algorithmes exacts (non polynomiaux), des résultats de \mathcal{N P}-complétude, et des conditions suffisantes assurant l’existence de certains objets (arbre couvrant, chemin et cycle hamiltonien) sans conflits