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A Taxonomy of Cooperative Search Algorithms

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Book cover Hybrid Metaheuristics (HM 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3636))

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Abstract

A lot of heuristic approaches have been explored in the last two decades in order to tackle large size optimization problems. These areas include parallel meta-heuristics, hybrid meta-heuristic, and cooperative search algorithms. Different taxonomies have been proposed in the literature for parallel and hybrid meta-heuristics. In these taxonomies, one can realize that cooperative search algorithms lie somewhere in between. This paper looks at cooperative search algorithms as a stand alone area. Two different taxonomies of cooperative search algorithm are proposed based on two different criteria. Different implementations in this area are reported and classified using these taxonomies.

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Authors and Affiliations

  1. Dept. of Electrical and Computer Engineering, University of Waterloo, Waterloo, N2L 3G1, Canada

    Mohammed El-Abd & Mohamed Kamel

Authors
  1. Mohammed El-Abd
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  2. Mohamed Kamel
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Editor information

Editors and Affiliations

  1. Universitat Politècnica de Catalunya, Barcelona, Spain

    María J. Blesa

  2. ALBCOM, Dept. Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, Barcelona, Spain

    Christian Blum

  3. DEIS, Campus of Cesena Alma Mater Studiorum, Università di Bologna, Cesena, Italy

    Andrea Roli

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

    Michael Sampels

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© 2005 Springer-Verlag Berlin Heidelberg

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El-Abd, M., Kamel, M. (2005). A Taxonomy of Cooperative Search Algorithms. In: Blesa, M.J., Blum, C., Roli, A., Sampels, M. (eds) Hybrid Metaheuristics. HM 2005. Lecture Notes in Computer Science, vol 3636. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546245_4

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  • DOI: https://doi.org/10.1007/11546245_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28535-9

  • Online ISBN: 978-3-540-31898-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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