NDLI: DAMS: distributed adaptive metaheuristic selection

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DAMS: distributed adaptive metaheuristic selection

Content Provider	ACM Digital Library
Author	Verel, Sébastien Derbel, Bilel
Abstract	We present a distributed algorithm, Select Best and Mutate (SBM), in the Distributed Adaptive Metaheuristic Selection (DAMS) framework. DAMS is dedicated to adaptive optimization in distributed environments. Given a set of metaheuristics, 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 nodes to decide distributively what local information to communicate, and what metaheuristic to apply while the optimization process is in progress. 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. SBM features are analyzed from both a parallel and an adaptive point of view, and its efficiency is demonstrated through experimentations and comparisons with other adaptive strategies (sequential and distributed).
Starting Page	1955
Ending Page	1962
Page Count	8
File Format	PDF
ISBN	9781450305570
DOI	10.1145/2001576.2001839
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-07-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Metaheurististics Adaptative algorithms Parameter control Distributed algorithms
Content Type	Text
Resource Type	Article

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