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Incorporating Preferences to a Multi-objective Ant Colony Algorithm for Time and Space Assembly Line Balancing

  • Manuel Chica
  • Óscar Cordón
  • Sergio Damas
  • Jordi Pereira
  • Joaquín Bautista
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5217)

Abstract

We present an extension of a multi-objective algorithm based on Ant Colony Optimisation to solve a more realistic variant of a classical industrial problem: Time and Space Assembly Line Balancing. We study the influence of incorporating some domain knowledge by guiding the search process of the algorithm with preferences-based dominance. Our approach is compared with other techniques, and every algorithm tackles a real-world instance from a Nissan plant. We prove that the embedded expert knowledge is even more justified in a real-world problem.

Keywords

Domain Knowledge Pareto Front Optimal Pareto Front Assembly Line Balance Assembly Line Balance Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Manuel Chica
    • 1
  • Óscar Cordón
    • 1
  • Sergio Damas
    • 1
  • Jordi Pereira
    • 2
  • Joaquín Bautista
    • 2
  1. 1.European Centre for Soft ComputingMieres (Asturias)Spain
  2. 2.Universitat Politècnica de CatalunyaBarcelonaSpain

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