Advertisement

International Conference on Theory and Application of Diagrams

Diagrams 2014: Diagrammatic Representation and Inference pp 16-30 | Cite as

Evolutionary Meta Layout of Graphs

  • Miro Spönemann
  • Björn Duderstadt
  • Reinhard von Hanxleden
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8578)

Abstract

A graph drawing library is like a toolbox, allowing experts to select and configure a specialized algorithm in order to meet the requirements of their diagram visualization application. However, without expert knowledge of the algorithms the potential of such a toolbox cannot be fully exploited. This gives rise to the question whether the process of selecting and configuring layout algorithms can be automated such that good layouts are produced. In this paper we call this kind of automation “meta layout.” We propose a genetic representation that can be used in meta heuristics for meta layout and contribute new metrics for the evaluation of graph drawings. Furthermore, we examine the use of an evolutionary algorithm to search for optimal solutions and evaluate this approach both with automatic experiments and a user study.

Keywords

graph drawing layout algorithms evolutionary algorithms meta layout readability metrics user study 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Biedl, T.C., Marks, J., Ryall, K., Whitesides, S.H.: Graph multidrawing: Finding nice drawings without defining nice. In: Whitesides, S.H. (ed.) GD 1998. LNCS, vol. 1547, pp. 347–355. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  2. 2.
    Purchase, H.C.: Metrics for graph drawing aesthetics. Journal of Visual Languages and Computing 13(5), 501–516 (2002)CrossRefGoogle Scholar
  3. 3.
    Barbosa, H.J.C., Barreto, A.M.S.: An interactive genetic algorithm with co-evolution of weights for multiobjective problems. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), pp. 203–210 (2001)Google Scholar
  4. 4.
    Branke, J., Bucher, F., Schmeck, H.: Using genetic algorithms for drawing undirected graphs. In: Proceedings of the Third Nordic Workshop on Genetic Algorithms and their Applications, pp. 193–206 (1996)Google Scholar
  5. 5.
    Eloranta, T., Mäkinen, E.: TimGA: A genetic algorithm for drawing undirected graphs. Divulgaciones Matemáticas 9(2), 155–170 (2001)MathSciNetzbMATHGoogle Scholar
  6. 6.
    Groves, L.J., Michalewicz, Z., Elia, P.V., Janikow, C.Z.: Genetic algorithms for drawing directed graphs. In: Proceedings of the 5th International Symposium on Methodologies for Intelligent Systems, pp. 268–276 (1990)Google Scholar
  7. 7.
    Rosete-Suarez, A., Ochoa-Rodriguez, A.: Genetic graph drawing. In: Nolan, P., Adey, R.A., Rzevski, G. (eds.) Applications of Artificial Intelligence in Engineering XIII, Software Studies, vol. 1. WIT Press / Computational Mechanics (1998)Google Scholar
  8. 8.
    Tettamanzi, A.G.: Drawing graphs with evolutionary algorithms. In: Parmee, I.C. (ed.) Adaptive Computing in Design and Manufacture, pp. 325–337. Springer, London (1998)CrossRefGoogle Scholar
  9. 9.
    Vrajitoru, D.: Multiobjective genetic algorithm for a graph drawing problem. In: Proceedings of the Midwest Artificial Intelligence and Cognitive Science Conference, pp. 28–43 (2009)Google Scholar
  10. 10.
    de Mendonça Neto, C.F.X., Eades, P.D.: Learning aesthetics for visualization. In: Anais do XX Seminário Integrado de Software e Hardware, pp. 76–88 (1993)Google Scholar
  11. 11.
    Utech, J., Branke, J., Schmeck, H., Eades, P.: An evolutionary algorithm for drawing directed graphs. In: Proceedings of the International Conference on Imaging Science, Systems, and Technology (CISST 1998), pp. 154–160. CSREA Press (1998)Google Scholar
  12. 12.
    de Mendonça Neta, B.M., Araujo, G.H.D., Guimarães, F.G., Mesquita, R.C., Ekel, P.Y.: A fuzzy genetic algorithm for automatic orthogonal graph drawing. Applied Soft Computing 12(4), 1379–1389 (2012)CrossRefGoogle Scholar
  13. 13.
    Bertolazzi, P., Di Battista, G., Liotta, G.: Parametric graph drawing. IEEE Transactions on Software Engineering 21(8), 662–673 (1995)CrossRefGoogle Scholar
  14. 14.
    Niggemann, O., Stein, B.: A meta heuristic for graph drawing: learning the optimal graph-drawing method for clustered graphs. In: Proceedings of the Working Conference on Advanced Visual Interfaces (AVI 2000), pp. 286–289. ACM, New York (2000)CrossRefGoogle Scholar
  15. 15.
    Archambault, D., Munzner, T., Auber, D.: Topolayout: Multilevel graph layout by topological features. IEEE Transactions on Visualization and Computer Graphics 13(2), 305–317 (2007)CrossRefGoogle Scholar
  16. 16.
    Barreto, A.M.S., Barbosa, H.J.C.: Graph layout using a genetic algorithm. In: Proc. of the 6th Brazilian Symposium on Neural Networks, pp. 179–184 (2000)Google Scholar
  17. 17.
    Dunne, C., Shneiderman, B.: Improving graph drawing readability by incorporating readability metrics: A software tool for network analysts. Tech. Rep. HCIL-2009-13, University of Maryland (2009)Google Scholar
  18. 18.
    Spönemann, M., Duderstadt, B., von Hanxleden, R.: Evolutionary meta layout of graphs. Technical Report 1401, Christian-Albrechts-Universität zu Kiel, Department of Computer Science (January 2014) ISSN 2192-6247Google Scholar
  19. 19.
    Masui, T.: Evolutionary learning of graph layout constraints from examples. In: Proceedings of the 7th Annual ACM Symposium on User Interface Software and Technology (UIST 1994), pp. 103–108. ACM (1994)Google Scholar
  20. 20.
    Gansner, E.R., North, S.C.: An open graph visualization system and its applications to software engineering. Software—Practice and Experience 30(11), 1203–1234 (2000)CrossRefGoogle Scholar
  21. 21.
    Chimani, M., Gutwenger, C., Jünger, M., Klau, G.W., Klein, K., Mutzel, P.: The Open Graph Drawing Framework (OGDF). In: Tamassia, R. (ed.) Handbook of Graph Drawing and Visualization, pp. 543–569. CRC Press (2013)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Miro Spönemann
    • 1
  • Björn Duderstadt
    • 1
  • Reinhard von Hanxleden
    • 1
  1. 1.Department of Computer ScienceChristian-Albrechts-Universität zu KielGermany

Personalised recommendations