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Ant Colony Optimization for the Total Weighted Tardiness Problem

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Parallel Problem Solving from Nature PPSN VI (PPSN 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1917))

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Abstract

In this article we present an application of the Ant Colony Optimization (ACO) metaheuristic to the single machine total weighted tardiness problem. First, we briefly discuss the constructive phase of ACO in which a colony of artificial ants generates a set of feasible solutions. Then, we introduce some simple but very effective local search. Last, we combine the constructive phase with local search obtaining a novel ACO algorithm that uses a heterogeneous colony of ants and is highly effective in finding the best-known solutions on all instances of a widely used set of benchmark problems.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Amsterdam, Kruislaan 403, NL-1098 SJ, Amsterdam, The Netherlands

    Matthijs den Besten

  2. IRIDIA, Université Libre de Bruxelles, Avenue Franklin Roosevelt 50, CP 194/6, 1050, Brussels, Belgium

    Matthijs den Besten, Thomas Stützle & Marco Dorigo

  3. Intellectics Group, Darmstadt University of Technology, Alexanderstr. 10, 64283, Darmstadt, Germany

    Thomas Stützle

Authors
  1. Matthijs den Besten
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  2. Thomas Stützle
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  3. Marco Dorigo
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Editor information

Editors and Affiliations

  1. CMAP, Ecole Polytechnique, 91128, Palaiseau Cedex, France

    Marc Schoenauer

  2. Dept. of Mechanical Engineering Kanpur Genetic Algorithms Laboratory, Indian Institute of Technology Kanpur, Kanpur, Pin, 208 016, India

    Kalyanmoy Deb

  3. Fachbereich Informatik, Lehrstuhl für Systemanalyse, Universität Dortmund, Joseph-von-Fraunhofer-Str. 20, 44221, Dortmund, Germany

    Günther Rudolph  & Hans-Paul Schwefel  & 

  4. School of Computer Science, The University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

    Xin Yao

  5. Projet Fractales, INRIA Rocquencourt, BP 105, 78153, Le Chesnay Cedex, France

    Evelyne Lutton

  6. Dept. de Arquitectura y Technologa de los Computadores, GeNeura Team, Universidad de Granada, Campus Fuenetenueva, s/n, Granada

    Juan Julian Merelo

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© 2000 Springer-Verlag Berlin Heidelberg

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den Besten, M., Stützle, T., Dorigo, M. (2000). Ant Colony Optimization for the Total Weighted Tardiness Problem. In: Schoenauer, M., et al. Parallel Problem Solving from Nature PPSN VI. PPSN 2000. Lecture Notes in Computer Science, vol 1917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45356-3_60

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  • DOI: https://doi.org/10.1007/3-540-45356-3_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41056-0

  • Online ISBN: 978-3-540-45356-7

  • eBook Packages: Springer Book Archive

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