Parallel Local Search

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 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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Chapitre d'ouvrage
Springer. Handbook of Parallel Constraint Reasoning, 2017
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http://hal.upmc.fr/hal-01511022
Contributeur : Philippe Codognet <>
Soumis le : jeudi 20 avril 2017 - 11:33:33
Dernière modification le : vendredi 21 avril 2017 - 10:27:13

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  • HAL Id : hal-01511022, version 1

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Philippe Codognet, Danny Munera, Daniel Diaz, Salvador Abreu. Parallel Local Search. Springer. Handbook of Parallel Constraint Reasoning, 2017. 〈hal-01511022〉

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