Robert J. Cimikowski

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We present a neural-network algorithm for minimizing edge crossings in drawings of nonplanar graphs. This is an important subproblem encountered in graph layout. The algorithm finds either the minimum number of crossings or an approximation thereof and also provides a linear embedding realizing the number of crossings found. The parallel time complexity of(More)
We present an empirical analysis of some heuristics for the graph thickness problem, i.e., decomposing a graph into the minimum number of planar subgraphs. The problem has applications in database systems, e.g., the layout of E-R diagrams. The heuristics are based on some algorithms for nding a maximal planar subgraph of a nonplanar graph. Empirical results(More)
|We present a neural network algorithm for minimizing edge crossings in drawings of nonplanar graphs. This is an important subproblem encountered in graph layout. The algorithm nds either the minimum number of crossings or an approximation thereof and also provides a linear embedding realizing the number of crossings found. The parallel time complexity of(More)
We present a randomized polynomial-time approximation algorithm for the fixed linear crossing number problem (FLCNP). In this problem, the vertices of a graph are placed in a fixed order along a horizontal “node line” in the plane, each edge is drawn as an arc in one of the two half-planes (pages), and the objective is to minimize the number of edge(More)