Search results for "Edge coloring"

showing 9 items of 9 documents

An exact method for graph coloring

2006

International audience; We are interested in the graph coloring problem. We propose an exact method based on a linear-decomposition of the graph. The complexity of this method is exponential according to the linearwidth of the entry graph, but linear according to its number of vertices. We present some experiments performed on literature instances, among which COLOR02 library instances. Our method is useful to solve more quickly than other exact algorithms instances with small linearwidth, such as mug graphs. Moreover, our algorithms are the first to our knowledge to solve the COLOR02 instance 4-Inser_3 with an exact method.

Discrete mathematics021103 operations research[INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO]General Computer Science0211 other engineering and technologies[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]0102 computer and information sciences02 engineering and technologyManagement Science and Operations Research01 natural scienceslaw.inventionCombinatoricsEdge coloring010201 computation theory & mathematicslawGraph powerModeling and SimulationLine graphGraph homomorphismGraph coloringFractional coloringGraph factorizationMathematicsList coloring[ INFO.INFO-RO ] Computer Science [cs]/Operations Research [cs.RO]
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Chromatic Sums for Colorings Avoiding Monochromatic Subgraphs

2013

Abstract Given graphs G and H, a vertex coloring c : V ( G ) → N is an H-free coloring of G if no color class contains a subgraph isomorphic to H. The H-free chromatic number of G, χ ( H , G ) , is the minimum number of colors in an H-free coloring of G. The H-free chromatic sum of G , Σ ( H , G ) , is the minimum value achieved by summing the vertex colors of each H-free coloring of G. We provide a general bound for Σ ( H , G ) , discuss the computational complexity of finding this parameter for different choices of H, and prove an exact formulas for some graphs G. For every integer k and for every graph H, we construct families of graphs, G k with the property that k more colors than χ ( …

Discrete mathematicsCombinatoricsGreedy coloringVertex (graph theory)Edge coloringApplied MathematicsDiscrete Mathematics and CombinatoricsMonochromatic colorChromatic scaleComplete coloringFractional coloringBrooks' theoremMathematicsElectronic Notes in Discrete Mathematics
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Logical definability of NP-optimisation problems with monadic auxiliary predicates

1993

Given a first-order formula ϕ with predicate symbols e1...el, so,...,sr, an NP-optimisation problem on -structures can be defined as follows: for every -structure G, a sequence of relations on G is a feasible solution iff satisfies ϕ, and the value of such a solution is defined to be ¦S0¦. In a strong sense, every polynomially bounded NP-optimisation problem has such a representation, however, it is shown here that this is no longer true if the predicates s1, ...,sr are restricted to be monadic. The result is proved by an Ehrenfeucht-Fraisse game and remains true in several more general situations.

Discrete mathematicsEdge coloringBounded functionPredicate (grammar)Clique numberNp optimization problemsMathematics
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On Coloring Unit Disk Graphs

1998

In this paper the coloring problem for unit disk (UD) graphs is considered. UD graphs are the intersection graphs of equal-sized disks in the plane. Colorings of UD graphs arise in the study of channel assignment problems in broadcast networks. Improving on a result of Clark et al. [2] it is shown that the coloring problem for UD graphs remains NP-complete for any fixed number of colors k≥ 3 . Furthermore, a new 3-approximation algorithm for the problem is presented which is based on network flow and matching techniques.

Discrete mathematicsGeneral Computer ScienceApplied MathematicsAstrophysics::Cosmology and Extragalactic AstrophysicsComplete coloring1-planar graphComputer Science ApplicationsBrooks' theoremCombinatoricsGreedy coloringIndifference graphEdge coloringChordal graphHigh Energy Physics::ExperimentGraph coloringMathematicsAlgorithmica
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Strong chromatic index of products of graphs

2007

Graphs and Algorithms

General Computer ScienceCritical graphKronecker product[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]strong productinduced matchingTheoretical Computer ScienceCombinatoricssymbols.namesakeComputer Science::Discrete MathematicsCartesian productDiscrete Mathematics and CombinatoricsChromatic scaleMathematicsDiscrete mathematicsKronecker productMathematics::Combinatoricslcsh:Mathematics[ INFO.INFO-DM ] Computer Science [cs]/Discrete Mathematics [cs.DM]Cartesian productlcsh:QA1-939Graph[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]Edge coloringMSC 05C15strong product.symbolsHypercubeStrong edge colouringMathematicsofComputing_DISCRETEMATHEMATICS
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A fast heuristic for solving the D1EC coloring problem

2010

In this paper we propose an efficient heuristic for solving the Distance-1 Edge Coloring problem (D1EC) for the on-the-fly assignment of orthogonal wireless channels in wireless as soon as a topology change occurs. The coloring algorithm exploits the simulated annealing paradigm, i.e., a generalization of Monte Carlo methods for solving combinatorial problems. We show that the simulated annealing-based coloring converges fast to a sub optimal coloring scheme even for the case of dynamic channel allocation. However, a stateful implementation of the D1EC scheme is needed in order to speed-up the network coloring upon topology changes. In fact, a stateful D1EC reduces the algorithm’s convergen…

Mathematical optimization:QA Mathematics::QA75 Electronic computers. Computer science [Q Science]TheoryofComputation_COMPUTATIONBYABSTRACTDEVICESChannel allocation schemesHeuristic (computer science)Computer scienceSettore ING-INF/03 - Telecomunicazioni:T Technology (General) [T Technology]Topology (electrical circuits)Greedy coloringEdge coloringTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESStateful firewall:Q Science (General) [Q Science]TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYConvergence (routing)Simulated annealing:TK Electrical engineering. Electronics Nuclear engineering [T Technology]Channel assignment Edge coloring Simulated annealing.MathematicsofComputing_DISCRETEMATHEMATICS
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A heuristic for fast convergence in interference-free channel assignment using D1EC coloring

2010

This work proposes an efficient method for solving the Distance-1 Edge Coloring problem (D1EC) for the assignment of orthogonal channels in wireless networks with changing topology. The coloring algorithm is performed by means of the simulated annealing method, a generalization of Monte Carlo methods for solving combinatorial problems. We show that the simulated annealing-based coloring converges fast to a suboptimal coloring scheme. Furthermore, a stateful implementation of the D1EC scheme is proposed, in which network coloring is executed upon topology changes. The stateful D1EC is also based on simulated annealing and reduces the algorithm’s convergence time by one order of magnitude in …

Mathematical optimizationSettore ING-INF/03 - TelecomunicazioniComputer scienceHeuristic (computer science)Wireless networkTopology (electrical circuits)[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationGreedy coloringEdge coloringStateful firewallSimulated annealingConvergence (routing)Channel assignment Edge coloring Simulated annealing.Algorithm
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Stochastic Learning for SAT- Encoded Graph Coloring Problems

2010

The graph coloring problem (GCP) is a widely studied combinatorial optimization problem due to its numerous applications in many areas, including time tabling, frequency assignment, and register allocation. The need for more efficient algorithms has led to the development of several GC solvers. In this paper, the authors introduce a team of Finite Learning Automata, combined with the random walk algorithm, using Boolean satisfiability encoding for the GCP. The authors present an experimental analysis of the new algorithm’s performance compared to the random walk technique, using a benchmark set containing SAT-encoding graph coloring test sets.

Statistics and ProbabilityDiscrete mathematicsControl and OptimizationTheoretical computer scienceComparability graphComputer Science ApplicationsGreedy coloringComputational MathematicsEdge coloringComputational Theory and MathematicsModeling and SimulationGraph (abstract data type)Decision Sciences (miscellaneous)Graph coloringFractional coloringGraph factorizationList coloringMathematicsInternational Journal of Applied Metaheuristic Computing
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The b-chromatic number of power graphs

2003

The b-chromatic number of a graph G is defined as the maximum number k of colors that can be used to color the vertices of G, such that we obtain a proper coloring and each color i, with 1 ≤ i≤ k, has at least one representant x_i adjacent to a vertex of every color j, 1 ≤ j ≠ i ≤ k. In this paper, we discuss the b-chromatic number of some power graphs. We give the exact value of the b-chromatic number of power paths and power complete binary trees, and we bound the b-chromatic number of power cycles.

b-chromatic numberGeneral Computer Science[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]power graphTheoretical Computer ScienceCombinatoricsComputer Science::Discrete MathematicsDiscrete Mathematics and CombinatoricsChromatic scaleGraph coloringcoloringMathematicscycle and complete binary treeMathematics::CombinatoricsBinary treelcsh:Mathematicscycle and complete binary tree.path[ INFO.INFO-DM ] Computer Science [cs]/Discrete Mathematics [cs.DM]Complete coloringlcsh:QA1-939Vertex (geometry)Brooks' theorem[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]Edge coloringFractional coloringDiscrete Mathematics & Theoretical Computer Science
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