Heuristic Approaches to Iterative Graph Drawing

NetvizGL is a C++ OpenGL application for the visualisation of network graphs. It is a lightweight application designed to be minimal, extensible and scalable. NetvizGL can draw networks per a set of graph drawing algorithms. These algorithms are either be pre-packaged or a user may choose to write their own. With an an adaptation mechanism in place a user can write a relatively small amount of code to integrate it into the framework. The application provides a highly interactive visual interface which allows to pan, zoom and rotate graph layouts, as well as to interactively edit colours and labels. Layouts can be export as either PNG images or vector graphics files.

We report on our findings using Simulated Annealing (SA) as a preprocessing step for force-directed graph drawing. Our proposed SA algorithm finds a smart initial vertex placement (instead of a random initial vertex placement) in order to decrease the chance of having edge crossings (local minima) and also to decrease the number of required iterations from start placement to the final placement.

We introduce a new force-directed graph drawing algorithm for large undirected graphs with at least a few hundreds of vertices. Our algorithm falls into the class of multilevel force-directed graph drawing algorithms. Unlike other multilevel algorithms it has no pre-processing step and it also ignores repulsion forces between pairs of non-adjacent vertices. As a result, our algorithm demonstrably outperforms known multilevel algorithms in terms of running time while keeping the quality of the layout sufficiently good.

We propose a genetic algorithm (GA) for solving the maximization version of the Optimal Linear Arrangement problem and we also demonstrate how solutions found by it can be used for constructing smart initial layouts for force-directed graph drawing. Effectively, we show that our GA can be used as a first step in force-directed graph drawing for achieving more aesthetically pleasing graph layouts at the end. We present experimental results which show that the initial layouts based on the solutions of our GA reduce the number of edge crossings in force-directed graph layouts.