Optimal Orthogonal Graph Drawing with Convex Bend Costs

Author:

Bläsius Thomas1,Rutter Ignaz1,Wagner Dorothea1

Affiliation:

1. Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

Abstract

Traditionally, the quality of orthogonal planar drawings is quantified by the total number of bends or the maximum number of bends per edge. However, this neglects that, in typical applications, edges have varying importance. We consider the problem O ptimal F lex D raw that is defined as follows. Given a planar graph G on n vertices with maximum degree 4 ( 4-planar graph ) and for each edge e a cost function cost e : N 0 → R defining costs depending on the number of bends e has, compute a planar orthogonal drawing of G of minimum cost. In this generality O ptimal F lex D raw is NP-hard. We show that it can be solved efficiently if (1) the cost function of each edge is convex and (2) the first bend on each edge does not cause any cost. Our algorithm takes time O ( n , ⋅, T flow ( n ) and O ( n 2 , ⋅, T flow ( n )) for biconnected and connected graphs, respectively, where T flow ( n ) denotes the time to compute a minimum-cost flow in a planar network with multiple sources and sinks. Our result is the first polynomial-time bend-optimization algorithm for general 4-planar graphs optimizing over all embeddings. Previous work considers restricted graph classes and unit costs.

Funder

GRADR-EUROGIGA

Publisher

Association for Computing Machinery (ACM)

Subject

Mathematics (miscellaneous)

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Topology-Shape-Metrics Framework for Ortho-Radial Graph Drawing;Discrete & Computational Geometry;2023-11-01

2. Level-Planar Drawings with Few Slopes;Algorithmica;2021-11-19

3. Extending Partial Orthogonal Drawings;Lecture Notes in Computer Science;2020

4. An Integer-Linear Program for Bend-Minimization in Ortho-Radial Drawings;Lecture Notes in Computer Science;2020

5. An SPQR-Tree-Like Embedding Representation for Upward Planarity;Lecture Notes in Computer Science;2019

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