Map-labelling with a multi-objective evolutionary algorithm

Authors:
Lucas Bradstreet;Luigi Barone;Lyndon While
Affiliations:
University of Western Australia, Crawley, Australia;University of Western Australia, Crawley, Australia;University of Western Australia, Crawley, Australia
Venue:
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Year:
2005

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Abstract

We present a multi-objective evolutionary algorithm approach to the map-labelling problem. Map-labelling involves placing labels for sites onto a map such that the result is easy to read and usable for navigation. However, map-users vary in their priorities and capabilities: for example, sight-impaired users need to maximise font-size, whereas other users may be willing to accept smaller labels in exchange for increased clarity of bindings of labels to sites. With a multi-objective approach, we evolve a range of labellings from which users can select according to their particular circumstances. We present results from labelling two maps, including a difficult, dense map of Newcastle County in Delaware, which clearly illustrate the advantages of the multi-objective approach.