Literature DB >> 20498505

Drawing and Labeling High-Quality Metro Maps by Mixed-Integer Programming.

M Nollenburg, A Wolff.   

Abstract

Metro maps are schematic diagrams of public transport networks that serve as visual aids for route planning and navigation tasks. It is a challenging problem in network visualization to automatically draw appealing metro maps. There are two aspects to this problem that depend on each other: the layout problem of finding station and link coordinates and the labeling problem of placing nonoverlapping station labels. In this paper, we present a new integral approach that solves the combined layout and labeling problem (each of which, independently, is known to be NP-hard) using mixed-integer programming (MIP). We identify seven design rules used in most real-world metro maps. We split these rules into hard and soft constraints and translate them into an MIP model. Our MIP formulation finds a metro map that satisfies all hard constraints (if such a drawing exists) and minimizes a weighted sum of costs that correspond to the soft constraints. We have implemented the MIP model and present a case study and the results of an expert assessment to evaluate the performance of our approach in comparison to both manually designed official maps and results of previous layout methods.

Year:  2010        PMID: 20498505     DOI: 10.1109/TVCG.2010.81

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  3 in total

1.  Metro maps of plant disease dynamics--automated mining of differences using hyperspectral images.

Authors:  Mirwaes Wahabzada; Anne-Katrin Mahlein; Christian Bauckhage; Ulrike Steiner; Erich-Christian Oerke; Kristian Kersting
Journal:  PLoS One       Date:  2015-01-26       Impact factor: 3.240

2.  Gaze-driven placement of items for proactive visual exploration.

Authors:  Shigeo Takahashi; Akane Uchita; Kazuho Watanabe; Masatoshi Arikawa
Journal:  J Vis (Tokyo)       Date:  2021-11-11       Impact factor: 1.974

3.  Uncluttered Single-Image Visualization of Vascular Structures Using GPU and Integer Programming.

Authors:  Joong-Ho Won; Yongkweon Jeon; Jarrett K Rosenberg; Sungroh Yoon; Geoffrey D Rubin; Sandy Napel
Journal:  IEEE Trans Vis Comput Graph       Date:  2012-01-31       Impact factor: 4.579

  3 in total

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