Hybrid algorithms for the minimum-weight rooted arborescence problem

Authors:
Sergi Mateo;Christian Blum;Pascal Fua;Engin Türetgen
Affiliations:
ALBCOM Research Group, Universitat Politéecnica de Catalunya, Barcelona, Spain;ALBCOM Research Group, Universitat Politéecnica de Catalunya, Barcelona, Spain;Computer Vision Lab, Ecole Polytechnique Fédérale de Lausanne, Switzerland;Computer Vision Lab, Ecole Polytechnique Fédérale de Lausanne, Switzerland
Venue:
ANTS'12 Proceedings of the 8th international conference on Swarm Intelligence
Year:
2012

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Abstract

Minimum-weight arborescence problems have recently enjoyed an increased attention due to their relation to imporant problems in computer vision. A prominent example is the automated reconstruction of consistent tree structures from noisy images. In this paper, we first propose a heuristic for tackling the minimum-weight rooted arborescence problem. Moreover, we propose an ant colony optimization algorithm. Both approaches are strongly based on dynamic programming, and can therefore be regarded as hybrid techniques. An extensive experimental evaluation shows that both algorithms generally improve over an exisiting heuristic from the literature.