Parallel Local Search

  • Philippe Codognet
  • Danny Munera
  • Daniel Diaz
  • Salvador Abreu


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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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Philippe Codognet
    • 1
  • Danny Munera
    • 2
  • Daniel Diaz
    • 3
  • Salvador Abreu
    • 4
  1. 1.University Pierre & Marie Curie/LIP6ParisFrance
  2. 2.University of AntioquiaMedellinColombia
  3. 3.University Paris 1/CRIParisFrance
  4. 4.University of Évora/LISP/CRIÉvoraPortugal

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