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Handbook of Parallel Constraint Reasoning pp 381–417Cite as

Parallel Local Search

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Abstract

Local search metaheuristics are a recognized means of solving hard combinatorial problems. Over the last couple of decades, significant advances have been made in terms of the formalization, applicability and performance of these methods. Key to the performance aspect is the increased availability of parallel hardware, which turns out to be largely exploitable by this class of procedures. As real-life cases of combinatorial optimization easily degrade into intractable territory for exact or approximation algorithms, local search metaheuristics hold undeniable interest. This situation is further compounded by the good adequacy exhibited by this class of search procedures for large-scale parallel operation. In this chapter we explore and discuss ways which lead to parallelization in local search

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Authors and Affiliations

  1. University Pierre & Marie Curie/LIP6, Paris, France

    Philippe Codognet

  2. University of Antioquia, Medellin, Colombia

    Danny Munera

  3. University Paris 1/CRI, Paris, France

    Daniel Diaz

  4. University of Évora/LISP/CRI, Évora, Portugal

    Salvador Abreu

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  1. Laboratoire d'informatique (LIX) de l'École polytechnique, Palaiseau, France

    Youssef Hamadi

  2. CRIL, CNRS UMR 8188, Université d'Artois, Lens, France

    Lakhdar Sais

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Codognet, P., Munera, D., Diaz, D., Abreu, S. (2018). Parallel Local Search. In: Hamadi, Y., Sais, L. (eds) Handbook of Parallel Constraint Reasoning. Springer, Cham. https://doi.org/10.1007/978-3-319-63516-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63515-6

  • Online ISBN: 978-3-319-63516-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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