@inproceedings{e6d04fd1031244a1b94f9e2d8a0a7fe9,
title = "A GA-inspired approach to the reduction of edge crossings in force-directed layouts",
abstract = "We report on our findings using a genetic algorithm (GA) as a preprocessing step for force-directed graph drawings to find a smart initial vertex layout (instead of a random initial layout) to decrease the number of edge crossings in the graph. We demonstrate that the initial layouts found by our GA improve the chances of finding better results in terms of the number of edge crossings, especially for sparse graphs and star-shaped graphs. In particular we demonstrate a reduction in edge-crossings for the class of star-shaped graphs by using our GA over random vertex placement in the order of 3:1.",
keywords = "Combinatorial optimization, Fitness evaluation, Genetic algorithms, Routing and layout, Running time analysis",
author = "{Ghassemi Toosi}, Farshad and Nikolov, {Nikola S.} and Malachy Eaton",
note = "Publisher Copyright: {\textcopyright} 2016 Copyright held by the owner/author(s).; 2016 Genetic and Evolutionary Computation Conference, GECCO 2016 Companion ; Conference date: 20-07-2016 Through 24-07-2016",
year = "2016",
month = jul,
day = "20",
doi = "10.1145/2908961.2908968",
language = "English",
series = "GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery, Inc",
pages = "89--90",
editor = "Tobias Friedrich",
booktitle = "GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference",
}