Dynamic variable ordering for ordered binary decision diagrams
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
An experimental comparison of four graph drawing algorithms
Computational Geometry: Theory and Applications
Arc crossing minimization in hierarchical digraphs with tabu search
Computers and Operations Research
A Technique for Drawing Directed Graphs
IEEE Transactions on Software Engineering
A Polyhedral Approach to the Multi-Layer Crossing Minimization Problem
GD '97 Proceedings of the 5th International Symposium on Graph Drawing
Fast and Simple Horizontal Coordinate Assignment
GD '01 Revised Papers from the 9th International Symposium on Graph Drawing
Crossing Reduction by Windows Optimization
GD '02 Revised Papers from the 10th International Symposium on Graph Drawing
Minimizing crossings in hierarchical digraphs with a hybridized genetic algorithm
Journal of Heuristics
Layer-free upward crossing minimization
Journal of Experimental Algorithmics (JEA)
Gravisto: graph visualization toolkit
GD'04 Proceedings of the 12th international conference on Graph Drawing
Crossing reduction in circular layouts
WG'04 Proceedings of the 30th international conference on Graph-Theoretic Concepts in Computer Science
The open graph archive: a community-driven effort
GD'11 Proceedings of the 19th international conference on Graph Drawing
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Directed graphs are commonly drawn by the Sugiyama algorithm where first vertices are placed on distinct hierarchical levels, and second vertices on the same level are permuted to reduce the overall number of crossings. Separating these two phases simplifies the algorithms but diminishes the quality of the result. We introduce a combined leveling and crossing reduction algorithm based on sifting, which prioritizes few crossings over few levels. It avoids type 2 conflicts, which are crossings of edges whose endpoints are dummy vertices. This helps straightening long edges spanning many levels. The obtained running time is roughly quadratic in the size of the input graph and independent of dummy vertices.