detalle del documento
IDENTIFICACIÓN
oai:HAL:hal-02179193v1
Tema
Big Optimization Quadratic assignment problem Iterative tabu search [INFO.INFO-AI]Computer Science [cs... [INFO.INFO-DC]Computer Science [cs... [INFO.INFO-RO]Computer Science [cs...Autor
Abdelkafi, Omar Derbel, Bilel Liefooghe, ArnaudLangue
enEditor
HAL CCSD
Categoría
CNRS - Centre national de la recherche scientifique
Año
2019
fecha de cotización
7/10/2023
Palabras clave
[info study [cs tabu science parallelResumen
International audience; Parallelization is an important paradigm for solving massive optimization problems.
Understanding how to fully benefit form the aggregated computing power and what makes a parallel strategy successful is a difficult issue.
In this study, we propose a simple parallel iterative tabu search (PITS) and study its effectiveness with respect to different experimental settings.
Using the quadratic assignment problem (QAP) as a case study, we first consider different small-and medium-size instances from the literature and then tackle a large-size instance that was rarely considered due the its inherent solving difficulty.
In particular, we show that a balance between the number of function evaluations each parallel process is allowed to perform before resuming the search is a critical issue to obtain an improved quality.
Abdelkafi, Omar,Derbel, Bilel,Liefooghe, Arnaud, 2019, A Parallel Tabu Search for the Large-scale Quadratic Assignment Problem, HAL CCSD
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