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Finding maximum-cardinality matchings in undirected graphs is arguably one of the most central graph problems. For general m-edge and n-vertex graphs, it is well known to be solvable in O(m√n) time. We present a linear-time algorithm to find maximum-cardinality matchings on cocomparability graphs, a prominent subclass of perfect graphs that strictly contains interval graphs as well as permutation graphs. Our greedy algorithm is based on the recently discovered Lexicographic Depth First Search (LDFS). [ABSTRACT FROM AUTHOR]

Tolerance graphs model interval relations in such a way that intervals can tolerate a certain amount of overlap without being in con ict. In one of the most natural generalizations of tolerance graphs with direct applications in the comparison of DNA sequences from different organisms, namely multitolerance graphs, two tolerances are allowed for each interval: one on the left side and the other on the right side. Several efficient algorithms for optimization problems that are NP-hard in general graphs have been designed for tolerance and multitolerance graphs. In spite of this progress, the complexity status of some fundamental algorithmic problems on tolerance and multitolerance graphs, such as the dominating set problem, remained unresolved until now--three decades after the introduction of tolerance graphs. In this paper we introduce two new geometric representations for tolerance and multitolerance graphs, given by points and line segments in the plane. Apart from being important on their own, these new representations prove to be a powerful tool for deriving both hardness results and polynomial time algorithms. Using them, we surprisingly prove that the dominating set problem can be solved in polynomial time on tolerance graphs and that it is APX-hard on multitolerance graphs, thus solving a longstanding open problem. This problem is the first one that has been discovered with a different complexity status in these two graph classes. [ABSTRACT FROM AUTHOR]

Intersection graphs of geometric objects have been extensively studied, due to both their interesting structure and their numerous applications; prominent examples include interval graphs and permutation graphs. In this paper we study a natural graph class that generalizes both interval and permutation graphs, namely simple-triangle graphs. Simple-triangle graphs--also known as PI (point-interval) graphs--are the intersection graphs of triangles that are defined by a point on a line L1 and an interval on a parallel line L2. They lie naturally between permutation and trapezoid graphs, which are the intersection graphs of line segments between L1 and L2 and of trapezoids between L1 and L2, respectively. Although various efficient recognition algorithms for permutation and trapezoid graphs are well known to exist, the recognition of simple-triangle graphs has remained an open problem since their introduction by Corneil and Kamula three decades ago. In this paper we resolve this problem by proving that simple-triangle graphs can be recognized in polynomial time. Given a graph G with n vertices, such that its complement G has m edges, our algorithm runs in O(n²m) time. As a consequence, our algorithm also solves a longstanding open problem in the area of partial orders, namely, the recognition of linear-interval orders, i.e., of partial orders P = P1 ∩ P2, where P1 is a linear order and P2 is an interval order. This is one of the first results on recognizing partial orders P that are the intersection of orders from two different classes P1 and P2 . In complete contrast to this, partial orders P which are the intersection of orders from the same class P have been extensively investigated, and in most cases the complexity status of these recognition problems has been already established. [ABSTRACT FROM AUTHOR]

Given a graph G, the longest path problem asks to compute a simple path of G with the largest number of vertices. This problem is the most natural optimization version of the well-known and well-studied Hamiltonian path problem, and thus it is NP-hard on general graphs. However, in contrast to the Hamiltonian path problem, there are only a few restricted graph families, such as trees, and some small graph classes where polynomial algorithms for the longest path problem have been found. Recently it has been shown that this problem can be solved in polynomial time on interval graphs by applying dynamic programming to a characterizing ordering of the vertices of the given graph [K. Ioannidou, G. B. Mertzios, and S. D. Nikolopoulos, Algorithmica, 61 (2011), pp. 320-341], thus answering an open question. In the present paper, we provide the first polynomial algorithm for the longest path problem on a much greater class, namely on cocomparability graphs. Our algorithm uses a similar, but essentially simpler, dynamic programming approach, which is applied to a lexicographic depth first search (LDFS) characterizing ordering of the vertices of a cocomparability graph. Therefore, our results provide evidence that this general dynamic programming approach can be used in a more general setting, leading to efficient algorithms for the longest path problem on greater classes of graphs. LDFS has recently been introduced in [D. G. Corneil and R. M. Krueger, SIAM J. Discrete Math., 22 (2008), pp. 1259-1276]. Since then, a similar phenomenon of extending an existing interval graph algorithm to cocomparability graphs by using an LDFS preprocessing step has also been observed for the minimum path cover problem [D. G. Corneil, B. Dalton, and M. Habib, submitted]. Therefore, more interestingly, our results also provide evidence that cocomparability graphs present an interval graph structure when they are considered using an LDFS ordering of their vertices, which may lead to other new and more efficient combinatorial algorithms. [ABSTRACT FROM AUTHOR]

Tolerance graphs model interval relations in such a way that intervals can tolerate a certain degree of overlap without being in conflict. This subclass of perfect graphs has been extensively studied, due to both its interesting structure and its numerous applications (in bioinformatics, constraint-based temporal reasoning, resource allocation, and scheduling problems, among others). Several efficient algorithms for optimization problems that are NP-hard in general graphs have been designed for tolerance graphs. In spite of this, the recognition of tolerance graphs--namely, the problem of deciding whether a given graph is a tolerance graph--as well as the recognition of their main subclass of bounded tolerance graphs, have been the most fundamental open problems on this class of graphs (cf. the book on tolerance graphs [M. C. Golumbic and A. N. Trenk, Tolerance Graphs, Cambridge Stud. Adv. Math. 89, Cambridge University Press, Cambridge, UK, 2004]) since their introduction in 1982 [M. C. Golumbic and C. L. Monma, Proceedings of the 13th Southeastern Conference on Combinatorics, Graph Theory and Computing, Congr. Numer., 35 (1982), pp. 321-331]. In this article we prove that both recognition problems are NP-complete, even in the case where the input graph is a trapezoid graph. The presented results are surprising because, on the one hand, most subclasses of perfect graphs admit polynomial recognition algorithms and, on the other hand, bounded tolerance graphs were believed to be efficiently recognizable as they are a natural special case of trapezoid graphs (which can be recognized in polynomial time) and share a very similar structure with them. For our reduction we extend the notion of an acyclic orientation of permutation and trapezoid graphs. Our main tool is a new algorithm that uses vertex splitting to transform a given trapezoid graph into a permutation graph, while preserving this new acyclic orientation property. This method of vertex splitting is of independent interest; very recently, it was also proved a powerful tool in the design of efficient recognition algorithms for other classes of graphs [ABSTRACT FROM AUTHOR]

Tolerance graphs model interval relations in such a way that intervals can tolerate a certain degree of overlap without being in conflict. This class of graphs, which generalizes in a natural way both interval and permutation graphs, has attracted many research efforts since their introduction in [M. C. Golumbic and C. L. Monma, Congr. Numer., 35 (1982), pp. 321-331], as it finds many important applications in constraint-based temporal reasoning, resource allocation, and scheduling problems, among others. In this article we propose the first non-trivial intersection model for general tolerance graphs, given by three-dimensional parallelepipeds, which extends the widely known intersection model of parallelograms in the plane that characterizes the class of bounded tolerance graphs. Apart from being important on its own, this new representation also enables us to improve the time complexity of three problems on tolerance graphs. Namely, we present optimal O(n log n) algorithms for computing a minimum coloring and a maximum clique and an O(n2) algorithm for computing a maximum weight independent set in a tolerance graph with n vertices, thus improving the best known running times O(n2) and O(n3) for these problems, respectively. [ABSTRACT FROM AUTHOR]