Evolving smart initial layouts for force-directed graph drawing

Farshad Ghassemi Toosi, Nikola S. Nikolov, Malachy Eaton

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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 forcedirected 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.

Original languageEnglish
Title of host publicationGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference
EditorsSara Silva
PublisherAssociation for Computing Machinery, Inc
Pages1397-1398
Number of pages2
ISBN (Electronic)9781450334884
DOIs
Publication statusPublished - 11 Jul 2015
Event17th Genetic and Evolutionary Computation Conference, GECCO 2015 - Madrid, Spain
Duration: 11 Jul 201515 Jul 2015

Publication series

NameGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference

Conference

Conference17th Genetic and Evolutionary Computation Conference, GECCO 2015
Country/TerritorySpain
CityMadrid
Period11/07/1515/07/15

Keywords

  • Combinatorial optimization
  • Fitness evaluation
  • Genetic algorithms
  • Routing and layout
  • Running time analysis

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