Partitionable graphs arising from near-factorizations of finite groups

AbstractIn 1979, two constructions for making partitionable graphs were introduced in (by Chvátal et al. (Ann. Discrete Math. 21 (1984) 197)). The graphs produced by the second construction are called CGPW graphs. A near-factorization (A,B) of a finite group is roughly speaking a non-trivial factorization of G minus one element into two subsets A and B. Every CGPW graph with n vertices turns out to be a Cayley graph of the cyclic group Zn, with connection set (A−A)⧹{0}, for a near-factorization (A,B) of Zn. Since a counter-example to the Strong Perfect Graph Conjecture would be a partitionable graph (Padberg, Math. Programming 6 (1974) 180), any ‘new’ construction for making partitionable graphs is of interest. In this paper, we investigate the near-factorizations of finite groups in general, and their associated Cayley graphs which are all partitionable. In particular, we show that near-factorizations of the dihedral groups produce every CGPW graph of even order. We present some results about near-factorizations of finite groups which imply that a finite abelian group with a near-factorization (A,B) such that |A|⩽4 must be cyclic (already proved by De Caen et al. (Ars Combin. 29 (1990) 53)). One of these results may be used to speed up exhaustive calculations. At last, we prove that there is no counter-example to the Strong Perfect Graph Conjecture arising from near-factorizations of a finite abelian group of even order

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

A Practical Hierarchial Model of Parallel Computation: The Model

We introduce a model of parallel computation that retains the ideal properties of the PRAM by using it as a sub-model, while simultaneously being more reflective of realistic parallel architectures by accounting for and providing abstract control over communication and synchronization costs. The Hierarchical PRAM (H-PRAM) model controls conceptual complexity in the face of asynchrony in two ways. First, by providing the simplifying assumption of synchronization to the design of algorithms, but allowing the algorithms to work asynchronously with each other; and organizing this control asynchrony via an implicit hierarchy relation. Second, by allowing the restriction of communication asynchrony in order to obtain determinate algorithms (thus greatly simplifying proofs of correctness). It is shown that the model is reflective of a variety of existing and proposed parallel architectures, particularly ones that can support massive parallelism. Relationships to programming languages are discussed. Since the PRAM is a sub-model, we can use PRAM algorithms as sub-algorithms in algorithms for the H-PRAM; thus results that have been established with respect to the PRAM are potentially transferable to this new model. The H-PRAM can be used as a flexible tool to investigate general degrees of locality (“neighborhoods of activity) in problems, considering communication and synchronization simultaneously. This gives the potential of obtaining algorithms that map more efficiently to architectures, and of increasing the number of processors that can efficiently be used on a problem (in comparison to a PRAM that charges for communication and synchronization). The model presents a framework in which to study the extent that general locality can be exploited in parallel computing. A companion paper demonstrates the usage of the H-PRAM via the design and analysis of various algorithms for computing the complete binary tree and the FFT/butterfly graph

Graph Theory

Highlights of this workshop on structural graph theory included new developments on graph and matroid minors, continuous structures arising as limits of finite graphs, and new approaches to higher graph connectivity via tree structures