A Tabu Search Based Approach for Graph Layout

This paper describes an automated tabu search based method for drawing general simple graph layouts with straight lines. To our knowledge, this is the first time tabu methods have been applied to graph drawing. We formulated the task as a multi-criteria optimization problem with a number of metrics which are used in a weighted fitness function to measure the aesthetic quality of the graph layout. The main goal of this work is speeding up the graph layout process without sacrificing the layout quality. To achieve this we used a tabu search based method that goes through a predefined number of iterations to minimize the value of the fitness function. Tabu search always chooses the best solution in the neighborhood. This may lead to cycling, so a tabu list is used to store moves that are not permitted so that the algorithm does not choose previous solutions for a set period of time. We give experimental results applied on random graphs and we provide statistical evidence that our method outperforms one of the fast search-based drawing methods (hill climbing) in execution time while it produces comparably good graph layouts. We also demonstrate the method on real world graph datasets. Keywords—Information visualization; graph drawing; graph layout; tabu search