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Titlebook: Algorithms and Discrete Applied Mathematics; First International Sumit Ganguly,Ramesh Krishnamurti Conference proceedings 2015 Springer In

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New Characterizations of Proper Interval Bigraphs and Proper Circular Arc Bigraphst no arc of the same partite set is properly contained in the other. In this paper, we characterize proper interval bigraphs and proper circular arc bigraphs using two linear orderings of their vertex set.
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https://doi.org/10.1007/978-3-642-51837-9lem in a simple cactus graph called .-cycle graph. For any originator we present a (2 − .)-approximation algorithm in the arbitrary .-cycle graph. We also prove that our algorithm generates the optimal broadcast time for some subclasses of this graph.
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Constant Approximation for Broadcasting in ,-cycle Graphlem in a simple cactus graph called .-cycle graph. For any originator we present a (2 − .)-approximation algorithm in the arbitrary .-cycle graph. We also prove that our algorithm generates the optimal broadcast time for some subclasses of this graph.
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On Collections of Polygons Cuttable with a Segment Saw sequence. In particular the same result holds for cutting with an arbitrary segment saw (of any length)..(III) In contrast, we show that there exist collections of disjoint rectangles (in arbitrary orientations) that are uncuttable by a segment saw. We also present various uncuttable collections of disjoint polygons, including triangles.
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Higher-Order Triangular-Distance Delaunay Graphs: Graph-Theoretical Propertiesn edge between two points if the interior of the smallest homothet of ∇ having the two points on its boundary contains at most . points of .. We consider the connectivity, Hamiltonicity and perfect-matching admissibility of ..TD. Finally we consider the problem of blocking the edges of ..TD.
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Probabilistic Arguments in Graph Coloring (Invited Talk),upper bounds but also in establishing the tightness of these upper bounds. It often calls for the application of various (often simple) ideas, tools and techniques (from probability theory) like moments, concentration inequalities, known estimates on tail probabilities and various other probability
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