An Evolutionary Algorithm for an Optimization Model of Edge Bundling

Joelma Ferreira, Hugo Nascimento, Les Foulds

Abstract

This paper presents two edge bundling optimization problems that address minimizing the total number of bundles, in conjunction with other aspects, as the main goal. A novel evolutionary edge bundling algorithm for these problems is described. The algorithm was successfully tested by solving two related problems applied to real-world instances in reasonable computational time. The development and analysis of optimization models have received little attention in the area of edge bundling. However, the reported experimental results demonstrate the effectiveness and the applicability of the proposed evolutionary algorithm to help resolve edge bundling problems formally defined as optimization models.

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Paper Citation


in Harvard Style

Ferreira J., Nascimento H. and Foulds L. (2018). An Evolutionary Algorithm for an Optimization Model of Edge Bundling.In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, ISBN 978-989-758-289-9, pages 132-143. DOI: 10.5220/0006626901320143


in Bibtex Style

@conference{ivapp18,
author={Joelma Ferreira and Hugo Nascimento and Les Foulds},
title={An Evolutionary Algorithm for an Optimization Model of Edge Bundling},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,},
year={2018},
pages={132-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006626901320143},
isbn={978-989-758-289-9},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,
TI - An Evolutionary Algorithm for an Optimization Model of Edge Bundling
SN - 978-989-758-289-9
AU - Ferreira J.
AU - Nascimento H.
AU - Foulds L.
PY - 2018
SP - 132
EP - 143
DO - 10.5220/0006626901320143