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Ant Colony Optimization for the Minimum-Weight Rooted Arborescence Problem

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Abstract

The minimum-weight rooted arborescence problem is an NP-hard combinatorial optimization problem which has important applications, for example, in computer vision. An example of such an application is the automated reconstruction of consistent tree structures from noisy images. In this chapter, we present an ant colony optimization approach to tackle this problem. Ant colony optimization is a metaheuristic which is inspired by the foraging behavior of ant colonies. By means of an extensive computational evaluation, we show that the proposed approach has advantages over an existing heuristic from the literature, especially for what concerns rather dense graphs.

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Abbreviations

ABC:

artificial bee colony

ACO:

ant colony optimization

cf:

convergence factor

DAG:

directed acyclic graph

DP:

dynamic programming

HCF:

hyper-cube framework

MMAS:

MAX-MIN ant system

MWRA:

minimum-weight rooted arborescence

PSO:

particle swarm optimization

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Author information

Authors and Affiliations

  1. Dep. Computer Science and Artificial Intelligence, University of the Basque Country, Paseo Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Christian Blum

  2. Dep. Computer Architecture, Polytechnic University of Catalonia, 08034, Barcelona, Spain

    Sergi Mateo Bellido

Authors
  1. Christian Blum
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  2. Sergi Mateo Bellido
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Corresponding author

Correspondence to Christian Blum .

Editor information

Editors and Affiliations

  1. Systems Research Inst., Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

  2. Dep. Electrical and Computer Engineering, University of Alberta, 116 Street 9107, T6J 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

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Blum, C., Mateo Bellido, S. (2015). Ant Colony Optimization for the Minimum-Weight Rooted Arborescence Problem. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_68

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  • DOI: https://doi.org/10.1007/978-3-662-43505-2_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43504-5

  • Online ISBN: 978-3-662-43505-2

  • eBook Packages: EngineeringEngineering (R0)

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