DAMS: Distributed Adaptive Metaheuristic Selection

Bilel Derbel 1, 2 Sébastien Verel 1, 3
1 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
Abstract : We present a distributed generic algorithm called DAMS dedicated to adaptive optimization in distributed environments. Given a set of metaheuristic, the goal of DAMS is to coordinate their local execution on distributed nodes in order to optimize the global performance of the distributed system. DAMS is based on three-layer architecture allowing node to decide distributively what local information to communicate, and what metaheuristic to apply while the optimization process is in progress. The adaptive features of DAMS are first addressed in a very general setting. A specific DAMS called SBM is then described and analyzed from both a parallel and an adaptive point of view. SBM is a simple, yet efficient, adaptive distributed algorithm using an exploitation component allowing nodes to select the metaheuristic with the best locally observed performance, and an exploration component allowing nodes to detect the metaheuristic with the actual best performance. The efficiency of BSM-DAMS is demonstrated through experimentations and comparisons with other adaptive strategies (sequential and distributed).
Type de document :
Communication dans un congrès
Genetic And Evolutionary Computation Conference, Jun 2011, Dublin, Ireland. ACM, pp.1955--1962, 2011, <10.1145/2001576.2001839>
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Contributeur : Sébastien Verel <>
Soumis le : mercredi 18 juillet 2012 - 17:03:09
Dernière modification le : samedi 16 janvier 2016 - 01:09:57
Document(s) archivé(s) le : vendredi 19 octobre 2012 - 02:21:17


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Bilel Derbel, Sébastien Verel. DAMS: Distributed Adaptive Metaheuristic Selection. Genetic And Evolutionary Computation Conference, Jun 2011, Dublin, Ireland. ACM, pp.1955--1962, 2011, <10.1145/2001576.2001839>. <hal-00579993>



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