The stable set polytope and some operations on graphs

AbstractWe study some operations on graphs in relation to the stable set polytope, for instance, identification of two nodes, linking a pair of nodes by an edge and composition of graphs by subgraph identification. We show that, with appropriate conditions, the descriptions of the stable set polytopes associated with the resulting graphs can be derived from those related to the initial graphs by adding eventual clique inequalities. Thus, perfection and h-perfection of graphs are preserved

An integer analogue of Carathéodory's theorem

AbstractWe prove a theorem on Hilbert bases analogous to Carathéodory's theorem for convex cones. The result is used to give an upper bound on the number of nonzero variables needed in optimal solutions to integer programs associated with totally dual integral systems. For integer programs arising from perfect graphs the general bounds are improved to show that if G is a perfect graph with n nodes and w is a vector of integral node weights, then there exists a minimum w-covering of the nodes that uses at most n distinct cliques

SIALAC Benchmark: On the design of adaptive algorithms for traffic lights problems

International audienceOptimizing traffic lights in road intersections is a mandatory step to achieve sustainable mobility and efficient public transportation in modern cities. Several mono or multi-objective optimization methods exist to find the best traffic signals settings, such as evolutionary algorithms, fuzzy logic algorithms, or even particle swarm optimizations. However, they are generally dedicated to very specific traffic configurations. In this paper, we introduce the SIALAC benchmark bringing together about 24 real-world based study cases, and investigate fitness landscapes structure of these problem instances

Combinatorial Surrogate-Assisted Optimization for Bus Stops Spacing Problem

International audienceThe distribution of transit stations constitutes an ubiquitous task in large urban areas. In particular, bus stops spacing is a crucial factor that directly affects transit ridership travel time. Hence, planners often rely on traffic surveys and virtual simulations of urban journeys to design sustainable public transport routes. However, the combinator-ial structure of the search space in addition to the time-consuming and black-box traffic simulations require computationally expensive efforts. This imposes serious constraints on the number of potential configurations to be explored. Recently, powerful techniques from discrete optimization and machine learning showed convincing to overcome these limitations. In this preliminary work, we build combinatorial surrogate models to approximate the costly traffic simulations. These so-trained surrog-ates are embedded in an optimization framework. More specifically, this article is the first to make use of a fresh surrogate-assisted optimization algorithm based on the mathematical foundations of discrete Walsh functions in order to solve the real-world bus stops spacing optimization problem. We conduct our experiments with the sialac benchmark in the city of Calais, France. We compare state-of-the-art approaches and we highlight the accuracy and the optimization efficiency of the proposed methods

Stable Set Bonding in Perfect Graphs and Parity Graphs

AbstractLet G1 = (V1 ∪ S1, E1) and G2 = (V2 ∪ S2, E2) be connected graphs which each have stable sets S1 (resp. S2) of the same size. Let ΦS be the operation which forms G = (V, E) from G1 and G2 by identification of S1 and S2, where S ⊆ V corresponds to S1 and S2. If all minimal chains in G1 and G2, linking v to w for v, w ∈ S have the same parity, and if H1 and H2 are parity graphs where G1 ΦSH2, H1 ΦSG2, and H1 ΦSH2 are perfect graphs then G1 ΦSG2, is also perfect. This leads to a new composition operation which preserves perfection

Arboricity, h-Index, and Dynamic Algorithms

In this paper we present a modification of a technique by Chiba and Nishizeki [Chiba and Nishizeki: Arboricity and Subgraph Listing Algorithms, SIAM J. Comput. 14(1), pp. 210--223 (1985)]. Based on it, we design a data structure suitable for dynamic graph algorithms. We employ the data structure to formulate new algorithms for several problems, including counting subgraphs of four vertices, recognition of diamond-free graphs, cop-win graphs and strongly chordal graphs, among others. We improve the time complexity for graphs with low arboricity or h-index.Comment: 19 pages, no figure

High performance genetic programming on GPU

The availability of low cost powerful parallel graphics cards has stimulated the port of Genetic Programming (GP) on Graphics Processing Units (GPUs). Our work focuses on the possibilities offered by Nvidia G80 GPUs when pro-grammed in the CUDA language. We compare two par-allelization schemes that evaluate several GP programs in parallel. We show that the fine grain distribution of compu-tations over the elementary processors greatly impacts per-formances. We also present memory and representation op-timizations that further enhance computation speed, up to 2.8 billion GP operations per second. The code has been developed with the well known ECJ library