Clique-circulants and the stable set polytope of fuzzy circular interval graphs

In this paper, we give a complete and explicit description of the rank facets of the stable set polytope for a class of claw-free graphs, recently introduced by Chudnovsky and Seymour (Proceedings of the Bristish Combinatorial Conference, 2005), called fuzzy circular interval graphs. The result builds upon the characterization of minimal rank facets for claw-free graphs by Galluccio and Sassano (J. Combinatorial Theory 69:1-38, 2005) and upon the introduction of a superclass of circulant graphs that are called clique-circulants. The new class of graphs is invetigated in depth. We characterize which clique-circulants C are facet producing, i.e. are such that Sigma upsilon epsilon V(C) chi(upsilon) <= alpha(C) is a facet of STAB(C), thus extending a result of Trotter (Discrete Math. 12:373-388, 1975) for circulants. We show that a simple clique family inequality (Oriolo, Discrete Appl. Math. 132(2):185-201, 2004) may be associated with each clique-circulant C subset of G, when G is fuzzy circular interval. We show that these inequalities provide all the rank facets of STAB(G), if G is a fuzzy circular interval graph. Moreover we conjecture that, in this case, they also provide all the non-rank facets of STAB(G) and offer evidences for this conjecture

The Strong Perfect Graph Conjecture: 40 years of Attempts, and its Resolution

International audienceThe Strong Perfect Graph Conjecture (SPGC) was certainly one of the most challenging conjectures in graph theory. During more than four decades, numerous attempts were made to solve it, by combinatorial methods, by linear algebraic methods, or by polyhedral methods. The first of these three approaches yielded the first (and to date only) proof of the SPGC; the other two remain promising to consider in attempting an alternative proof. This paper is an unbalanced survey of the attempts to solve the SPGC; unbalanced, because (1) we devote a signicant part of it to the 'primitive graphs and structural faults' paradigm which led to the Strong Perfect Graph Theorem (SPGT); (2) we briefly present the other "direct" attempts, that is, the ones for which results exist showing one (possible) way to the proof; (3) we ignore entirely the "indirect" approaches whose aim was to get more information about the properties and structure of perfect graphs, without a direct impact on the SPGC. Our aim in this paper is to trace the path that led to the proof of the SPGT as completely as possible. Of course, this implies large overlaps with the recent book on perfect graphs [J.L. Ramirez-Alfonsin and B.A. Reed, eds., Perfect Graphs (Wiley & Sons, 2001).], but it also implies a deeper analysis (with additional results) and another viewpoint on the topic

Characterizing Structurally Cohesive Clusters in Networks: Theory and Algorithms

This dissertation aims at developing generalized network models and solution approaches for studying cluster detection problems that typically arise in networks. More specifically, we consider graph theoretic relaxations of clique as models for characterizing structurally cohesive and robust subgroups, developing strong upper bounds for the maximum clique problem, and present a new relaxation that is useful in clustering applications. We consider the clique relaxation models of k-block, and k-robust 2-club for describing cohesive clusters that are reliable and robust to disruptions, and introduce a new relaxation called s-stable cluster, for modeling stable clusters. First, we identify the structural properties associated with the models, and investigate the computational complexity of these problems. Next, we develop mathematical programming techniques for the optimization problems introduced, and apply them in presenting effective solution approaches to the problems. We present integer programming formulations for the optimization problems of interest, and provide a detailed study of the associated polytopes. Particularly, we develop valid inequalities and identify different classes of facets for the polytopes. Exact solution approaches developed for solving the problems include simple branch and bound, branch and cut, and combinatorial branch and bound algorithms. In addition, we introduce many preprocessing techniques and heuristics to enhance their performance. The presented algorithms are tested computationally on a number of graph instances, that include social networks and random graphs, to study the capability of the proposed solution methods. As a fitting conclusion to this work, we propose new techniques to get easily computable and strong upper bounds for the maximum clique problem. We investigate k-core and its stronger variant k-core/2-club in this light, and present minimization problems to get an upper bound on the maximization problems. Simple linear programming relaxations are developed and strengthened by valid inequalities, which are then compared with some standard relaxations from the literature. We present a detailed study of our computational results on a number of benchmark instances to test the effectiveness of our technique for getting good upper bounds

Combinatorics

[no abstract available