A relationship between triangulated graphs,comparability graphs,proper interval graphs,proper circular-arc graphs,and nested interval graphs

Given a set F of digraphs, we say a graph G is a F-graph (resp., F*-graph) if it has an orientation (resp., acyclic orientation) that has no induced subdigraphs isomorphic to any of the digraphs in F. It is proved that all the classes of graphs mentioned in the title are F-graphs or F*-graphs for subsets F of a set of three digraphs.     

On-line algorithms for ordered sets and comparability graphs

We discuss several results concerning on-line algorithms for ordered sets and comparability graphs. The main new result is on the problem of on-line transitive orientation. We view on-line transitive orientation of a comparability graph G as a two-person game. In the ith round of play, 1 i | V(G)|, player A names a graph G_i such that G_i is isomorphic to a subgraph of G, |V(G_i)| = i, and G_i−1 is an induced subgraph of G_i if i> 1. Player B must respond with a transitive orientation of G_i which extends the transitive orientation given to G_i−1 in the previous round of play. Player A wins if and only if player B fails to give a transitive orientation to G_i for some i, 1 i |V(G)|. Our main result shows that player A has at most three winning moves. We also discuss applications to on-line clique covering of comparability graphs, and we mention some open problems.     

Certifying algorithms for recognizing proper circular-arc graphs and unit circular-arc graphs

We give two new linear-time algorithms, one for recognizing proper circular-arc graphs and the other for recognizing unit circular-arc graphs. Both algorithms provide either a model for the input graph, or a certificate that proves that such a model does not exist and can be authenticated in O(n) time. No other previous algorithm for each of these two graph classes provides a certificate for its result.     

Metric characterizations of proper interval graphs and tree-clique graphs

A connected graph G is a tree-clique graph if there exists a spanning tree T (a compatible tree) such that every clique of G is a subtree of T. When T is a path the connected graph G is a proper interval graph which is usually defined as intersection graph of a family of closed intervals of the real line such that no interval contains another. We present here metric characterizations of proper interval graphs and extend them to tree-clique graphs. This is done by demonstrating “local” properties of tree-clique graphs with respect to the subgraphs induced by paths of a compatible tree. © 1996 John Wiley & Sons, Inc.     

Polynomial algorithms for kernels in comparability, permutation and P 4-free graphs

In this paper, we give three polynomial algorithms which detect a kernel in comparability graphs relatively to an M-orientation, in permutation graphs and in P₄-free graphs with a normal orientation. MSC classification: 05C69, 05C85 Correspondence to: Saoula Youcef     

Stability in circular arc graphs

An algorithm is presented which finds a maximum stable set of a family of n arcs on a circle in O(nlogn) time given the arcs as an unordered list of their endpoints or in O(n) time if they are already sorted. If we are given only the circular arc graph without a circular arc representation for it, then a maximum stable set can be found in O(n + δe) time where n, e, and δ are the number of vertices, edges, and minimum vertex degree, respectively. Our algorithms are based on a simple neighborhood reduction theorem which allows one to reduce any circular arc graph to a special canonical form.     

Well covered simplicial,chordal, and circular arc graphs

A graph G is called well covered if every two maximal independent sets of G have the same number of vertices. In this paper, we characterize well covered simplicial, chordal and circular arc graphs. © 1996 John Wiley & Sons, Inc.     

Two remarks on circular arc graphs

In our first remark we observe a property of circular arcs which is similar to the Helly property and is helpful in describing all maximal cliques in circular arc graphs (as well as allowing us to genralize a result of Tucker). Our main result is a new simple characterization of circular arc graphs of clique covering number two. These graphs play a crucial role in recognition algorithms for circular arc graphs, and have been characterized by several authors. Specifically, we show that a graph with clique covering number two is a circular arc graph if and only if its edges can be coloured by two colours so that no induced four-cycle contains two opposite edges of the same colour. Our proof of the characterization depends on the lexicographic method we have recently introduced. Both remarks could be useful in designing efficient algorithms for (maximum cliques in, respectively recognition of) circular arc graphs     

Some parallel algorithms on interval graphs

Parallel algorithms are given for finding a maximum weighted clique, a maximum weighted independent set, a minimum clique cover, and a minimum weighted dominating set of an interval graph. Parallel algorithms are also given for finding a Hamiltonian circuit and the minimum bandwidth of a proper interval graph. The shared memory model (SMM) of parallel computers is used to obtain fast algorithms.     

A framework and algorithms for circular drawings of graphs

In this paper, we present a framework and two linear time algorithms for obtaining circular drawings of graphs. The first technique produces circular drawings of biconnected graphs and finds a zero crossing circular drawing if one exists. The second technique finds multiple embedding circle drawings. Techniques for the reduction of edge crossings are also discussed. Results of experimental studies are included.     

Stochastic service systems,random interval graphs and search algorithms

We consider several stochastic service systems, and study the asymptotic behavior of the moments of various quantities that have application to models for random interval graphs and algorithms for searching for an idle server or for an vacant or occupied waiting station. In some cases the moments turn out to involve Lambert series for the generating functions for the sums of powers of divisors of positive integers. For these cases we are able to obtain complete asymptotic expansions for the moments of the quantities in question. © 2013 Wiley Periodicals, Inc. Random Struct. Alg., 45, 421–442, 2014     

The Roberts characterization of proper and unit interval graphs

In this note, a constructive proof that the classes of proper interval graphs and unit interval graphs coincide is given, a result originally established by Fred S. Roberts. Additionally, the proof yields a linear-time and space algorithm to compute a unit interval representation, given a proper interval graph as input.     

An implicit representation of chordal comparability graphs in linear time

Ma and Spinrad have shown that every transitive orientation of a chordal comparability graph is the intersection of four linear orders. That is, chordal comparability graphs are comparability graphs of posets of dimension four. Among other uses, this gives an implicit representation of a chordal comparability graph using O(n) integers so that, given two vertices, it can be determined in O(1) time whether they are adjacent, no matter how dense the graph is. We give a linear time algorithm for finding the four linear orders, improving on their bound of O(n²).     

On the homogeneous representation of interval graphs

An interval graph G is homogeneously representable if for every vertex v of G there exists an interval representation of G with v corresponding to an end interval. We show that the homogeneous representation of interval graphs is rooted in a deeper property of a class of graphs that we characterize by forbidden configurations.     

A dynamic distributed approach to representing proper interval graphs

First studied by Brodal and Fagerberg [G.S. Brodal, R. Fagerberg, Dynamic representation of sparse graphs, in: Algorithms and Data Structures, Proceedings of the 6th International Workshop, Vancouver, Canada, in: Lecture Notes in Computer Science, vol. 1663, Springer-Verlag, 1999], a dynamic adjacency labelling scheme labels the vertices of a graph so that the adjacency of two vertices can be deduced from their labels. The scheme is dynamic in the sense that only a small adjustment must be made to the vertex labels when a small change is made to the graph.Using a centralized dynamic representation of Hell, Shamir and Sharan [P. Hell, R. Shamir, R. Sharan, A fully dynamic algorithm for recognizing and representing proper interval graphs, SIAM Journal on Computing 31 (1) (2001) 289-305], we develop a bit/label dynamic adjacency labelling scheme for proper interval graphs. Our fully dynamic scheme handles vertex deletion/addition and edge deletion/addition in time. Furthermore, our dynamic scheme is error-detecting, as it recognizes when the new graph is not a proper interval graph.     

Dominating sets and domatic number of circular arc graphs

A dominating set of a graph G = (N,E) is a subset S of nodes such that every node is either in S or adjacent to a node which is in S. The domatic number of G is the size of a maximum cardinality partition of N into dominating sets. The problems of finding a minimum cardinality dominating set and the domatic number are both NP-complete even for special classes of graphs. In the present paper we give an O(n∣E∣) time algorithm that finds a minimum cardinality dominating set when G is a circular arc graph (intersection graph of arcs on a circle). The domatic number problem is solved in O(n² log n) time when G is a proper circular arc graph, and it is shown NP-complete for general circular arc graphs.     

On the recognition of fuzzy circular interval graphs

Fuzzy circular interval graphs are a generalization of proper circular arc graphs and have been recently introduced by Chudnovsky and Seymour as a fundamental subclass of claw-free graphs. In this paper, we provide a polynomial time algorithm for recognizing such graphs, and more importantly for building a suitable model for these graphs.