A fine-grained message passing MOEA/D

Bilel Derbel 1 Arnaud Liefooghe 1 Gauvain Marquet 1 El-Ghazali Talbi 1
1 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : We propose the first large-scale message passing distributed scheme for parallelizing the computational flow of MOEA/D, a popular decomposition-based evolutionary multi-objective optimization algorithm. We show how synchronicity and workload granularity can impact both quality and computing time, in an extremely fine-grained configuration where each individual in the MOEA/D population is mapped to a single distributed processing unit. More specifically, we deploy our distributed protocol using a large-scale environment of 128 computing cores and conduct a throughout analysis using a broad range of bi-objective combinatorial ρMNK-landscapes. Besides being able to show significant speed-ups while maintaining competitive search quality, our experimental results provide insights into the behavior of the proposed scheme in terms of quality/speed-up trade-offs; thus pushing a step towards the achievement of effective and efficient parallel decomposition-based approaches for large-scale multi-objective optimization.
Type de document :
Communication dans un congrès
IEEE Congress on Evolutionary Computation (CEC 2015), May 2015, Sendai, Japan. pp.1837-1844, 2015, IEEE Congress on Evolutionary Computation (CEC 2015)
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Contributeur : Arnaud Liefooghe <>
Soumis le : mercredi 4 janvier 2017 - 14:39:11
Dernière modification le : vendredi 22 mars 2019 - 01:34:49
Document(s) archivé(s) le : mercredi 5 avril 2017 - 12:04:17

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Bilel Derbel, Arnaud Liefooghe, Gauvain Marquet, El-Ghazali Talbi. A fine-grained message passing MOEA/D. IEEE Congress on Evolutionary Computation (CEC 2015), May 2015, Sendai, Japan. pp.1837-1844, 2015, IEEE Congress on Evolutionary Computation (CEC 2015). 〈hal-01151874〉

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