Parallel Local Search - Sorbonne Université
Chapitre D'ouvrage Année : 2018

Parallel Local Search

Philippe Codognet
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Daniel Diaz

Résumé

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 the real-life cases of combinatorial optimisation 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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Dates et versions

hal-01511022 , version 1 (20-04-2017)

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Citer

Philippe Codognet, Danny Munera, Daniel Diaz, Salvador Abreu. Parallel Local Search. Handbook of Parallel Constraint Reasoning, Springer International Publishing, pp.381-417, 2018, 978-3-319-63515-6. ⟨10.1007/978-3-319-63516-3_10⟩. ⟨hal-01511022⟩
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