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Ant Colonies for the RCPS Problem

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Topics in Artificial Intelligence (CCIA 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2504))

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Abstract

Several approaches based on Ant Colony Optimization (ACO) are developed to solve the Resource Constrained Project Scheduling Problem (RCPSP). Starting from two different proposals of the metaheuristic, four different algorithms adapted to the problem characteristics are designed and implemented. Finally the effectiveness of the algorithms are tested comparing its results with those previously found in the literature for a data set used as a the benchmark instance set for the problem.

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Author information

Authors and Affiliations

  1. ETSEIB, Universitat Politécnica de Catalunya, Avda. Diagonal 647, Planta 7, 08028, Barcelona, Spain

    Joaquín Bautista & Jordi Pereira

Authors
  1. Joaquín Bautista
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  2. Jordi Pereira
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Editor information

Editors and Affiliations

  1. Departament d’Enginyeria i Ciència dels Computadors, Universitat Jaume 1, Campus de Riu Sec, 12071, Castellón, Spain

    M. Teresa Escrig  & Francisco Toledo  & 

  2. Computer Science Department, Universitat Ramon Llull, Passeig Bonanova, 8, 08022, Barcelona, Catalunya, Spain

    Elisabet Golobardes

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© 2002 Springer-Verlag Berlin Heidelberg

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Bautista, J., Pereira, J. (2002). Ant Colonies for the RCPS Problem. In: Escrig, M.T., Toledo, F., Golobardes, E. (eds) Topics in Artificial Intelligence. CCIA 2002. Lecture Notes in Computer Science(), vol 2504. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36079-4_23

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  • DOI: https://doi.org/10.1007/3-540-36079-4_23

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00011-2

  • Online ISBN: 978-3-540-36079-7

  • eBook Packages: Springer Book Archive

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