Parallel Local Search

• Autor(es): Codognet, Philippe ; Munera, Danny ; Diaz, Daniel ; Abreu, Salvador
• Data: 2018
• Identificador Persistente: http://hdl.handle.net/10174/22719
• Origem: Repositório Científico da Universidade de Évora
• Tipo de Documento: Capitulo
• Idioma: Inglês

Descrição

Local search metaheuristics are a recognized means of solving hard com- binatorial 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.