In the Directed Steiner Tree problem, we are given a directed graph G = (V,E) with edge costs, a root vertex r ∈ V, and a terminal set X ⊆ V . The goal is to find the cheapest subset of edges that contains an r-t path for every terminal t ∈ X. The only known polylogarithmic approximations for Directed Steiner Tree run in quasi-polynomial time and the best polynomial time approximations only achieve a guarantee of O(|X|^ε) for any constant ε > 0. Furthermore, the integrality gap of a natural LP relaxation can be as bad as Ω(√|X|).  We demonstrate that l rounds of the Sherali-Adams hierarchy suffice to reduce the integrality gap of a natural LP relaxation for Directed Steiner Tree in l-layered graphs from Ω( k) to O(l · log k) where k is the number of terminals. This is an improvement over Rothvoss’ result that 2l rounds of the considerably stronger Lasserre SDP hierarchy reduce the integrality gap of a similar formulation to O(l · log k). We also observe that Directed Steiner Tree instances with 3 layers of edges have only an O(logk) integrality gap bound in the standard LP relaxation, complementing the fact that the gap can be as large as Ω(√k) in graphs with 4 layers. Finally, we consider quasi-bipartite instances of Directed Steiner Tree meaning no edge in E connects two Steiner nodes V − (X ∪ {r}). By a simple reduction from Set Cover, it is still NP-hard to approximate quasi-bipartite instances within a ratio better than O(log|X|). We present a polynomial-time O(log |X|)-approximation for quasi-bipartite instances of Directed Steiner Tree. Our approach also bounds the integrality gap of the natural LP relaxation by the same quantity. A novel feature of our algorithm is that it is based on the primal-dual framework, which typically does not result in good approximations for network design problems in directed graphs.

Dans un graphe orienté contenant un nœud appelé racine, un sous ensemble de nœuds appelés terminaux et une pondération sur les arcs, le problème de l’arborescence de Steiner (DST) consiste en la recherche d’une arborescence de poids minimum contenant pour chaque terminal un chemin de la racine vers ce terminal. Ce problème est NP-Complet. Cette thèse se penche sur l’étude de l’approximabilité de ce problème. Sauf si P=NP, il n’existe pas pour ce problème d’approximation de rapport constant ou logarithmique en k, oú k est le nombre de terminaux. Le plus petit rapport d’approximation connu est O (k") où " est un réel strictement positif. Dans la première partie, nous donnons trois algorithmes d’approximation : un algorithme glouton efficace qui associe deux techniques d’approximations connues pour DST, un algorithme dans le cas des graphes structurés en paliers qui étudie l’approximabilité du problème quand les terminaux sont éloignés de la racine, et un algorithme exponentiel qui combine un algorithme d’approximation et un algorithme exact, dont le rapport d’approximation et la complexité temporelle sont paramétrés par le nombre de terminaux couverts par l’algorithme exact. Dans la seconde partie, nous étudions deux problèmes issus de DST auquel est ajoutée une contrainte sur les nœuds de branchement. Cette contrainte réduit le nombre de solutions réalisables et peut faciliter la recherche d’une solution optimale parmi ce sous-ensemble de solutions. En fonction de la contrainte, nous étudions la possibilité de la trouver en temps polynomial et quel est le rapport d’approximation entre cette solution et la solution du problème non contraint / The directed Steiner tree problem (DST) asks, considering a directed weighted graph, a node r called root and a set of nodes X called terminals, for a minimum cost directed tree rooted in r spanning X. DST is an NP-complete problem. We are interested in the search for polynomial approximations for DST. Unless P = NP, DST can not be approximated neither within a constant ratio nor a logarithmic ratio with respected to k, where k is the number of terminals. The smallest known approximation ratio is O(kԑ)$ where ԑ is a positive real.In the first part, we provide three new approximation algorithms : a practical greedy algorithm merging two of the main approximation techniques for DST, an algorithm for the case where the graph is layered and where the distance between the terminals and the root is high, and an exponential approximation algorithm combining an approximation algorithm and an exact algorithm, parameterized with the number of terminals the exact algorithm must cover.In the last part we study DST with two branching constraints. With this technique, we are able to reduce the number of feasible solutions, and possibly facilitate the search for an optimal solution of the constraint problem. We study how it is possible to build such a solution in polynomial time and if this solution is a good approximation of an optimal solution of the non-constraint problem