A multiobjective genetic algorithm for automatic orthogonal graph drawing

  • Authors:

  • Bernadete Maria de Mendonca Neta;Gustavo Henrique Diniz Araújo;Frederico Gadelha Guimaraes;Renato Cardoso Mesquita

  • Affiliations:

  • Universidade Federal de Minas Gerais, Belo Horizonte, Brazil;Universidade Federal de Minas Gerais, Belo Horizonte, Brazil;Universidade Federal de Minas Gerais, Belo Horizonte, Brazil;Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

  • Venue:
  • Proceedings of the 13th annual conference on Genetic and evolutionary computation
  • Year:
  • 2011

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Abstract

We present a multiobjective hybrid technique for automatic orthogonal graph drawing. The new methodology combines the classical approach to automatic orthogonal graph drawings,the topology-shape-metric approach, and a multiobjective genetic algorithm based on the NSGA-II method. In the topology-shape-metric method, a fixed planar embedding is obtained in the planarization step and submitted to the orthogonalization and compaction steps, in this order. In the hybrid approach, a greater number of planar embeddings is explored by varying the order of edges insertion that forms the planar embedding in the planarization step. The problem is then formulated as a multiobjective permutationbased combinatorial optimization problem, considering the minimization of the number of crossings, the number of bends and the area of the drawing. Solutions on the estimated Pareto front represent different drawings, that can be stored and selected by the user in real-time. We illustrate a possible multicriteria decision making based on fuzzy decision. The results show that the hybrid methodology using NSGA-II is able to find good and diverse solutions, when compared to the traditional topology-shape-metric method.