posted on 2006-09-27, 16:15authored byHongmei He, Matthew Newton, Ondrej Sykora
We design genetic algorithms with small populations for two
basic problems of graph drawing: the one-sided bipartite drawing and the
outerplanar drawing. We compare our results for the one-sided bipartite
drawing problem with Penalty Minimisation (PM)[3], the best one-sided
heuristic currently available. For graphs without a structural symmetry,
our genetic algorithm achieves drawings with lower numbers of crossings
than PM. If run on different initial random seeds and for a longer time, we
can achieve same results as PM for graphs with a symmetrical structure.
We compare performance of our genetic algorithm for the outerplanar
drawing with the previously known best heuristic algorithms such as [2]
and [7] on more important suites of graphs and get better results.
History
School
Science
Department
Computer Science
Pages
215163 bytes
Citation
HE, NEWTON and SÝKORA, 2005. Genetic algorithms for bipartite and outerplanar graph drawings are best! IN: Communications of the 31st Conference on Current Trends in Theory and Practice of Informatics (SOFSEM 2005), Liptovsky Jan, Slovakia, 22-28 January