research-article

DAMS: distributed adaptive metaheuristic selection

Authors:

Bilel Derbel,

Sébastien VerelAuthors Info & Claims

GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation

Pages 1955 - 1962

https://doi.org/10.1145/2001576.2001839

Published: 12 July 2011 Publication History

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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).

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Cited By

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Pontes RDuarte GGoliatt L(2020)Migration Guided by a Performance Index in Heterogeneous Island ModelsBioinspired Optimization Methods and Their Applications10.1007/978-3-030-63710-1_10(125-134)Online publication date: 16-Nov-2020
https://doi.org/10.1007/978-3-030-63710-1_10
Jankee CVerel SDerbel BFonlupt C(2018)On the Design of a Master-Worker Adaptive Algorithm Selection FrameworkArtificial Evolution10.1007/978-3-319-78133-4_1(1-15)Online publication date: 20-Mar-2018
https://doi.org/10.1007/978-3-319-78133-4_1
Jankee CVerel SDerbel BFlonlupt CEsparcia-Alcázar A(2015)New Adaptive Selection Strategies for Distributed Adaptive Metaheuristic SelectionProceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation10.1145/2739482.2764694(1405-1406)Online publication date: 11-Jul-2015
https://dl.acm.org/doi/10.1145/2739482.2764694
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Index Terms

DAMS: distributed adaptive metaheuristic selection
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction

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Published In

GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation

July 2011

2140 pages

ISBN:9781450305570

DOI:10.1145/2001576

Editor:
Natalio Krasnogor
University of Nottingham, UK
,
General Chair:
Pier Luca Lanzi
Politecnico di Milano, Italy

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2011

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GECCO '11

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SIGEVO

GECCO '11: Genetic and Evolutionary Computation Conference

July 12 - 16, 2011

Dublin, Ireland

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all

Pontes RDuarte GGoliatt L(2020)Migration Guided by a Performance Index in Heterogeneous Island ModelsBioinspired Optimization Methods and Their Applications10.1007/978-3-030-63710-1_10(125-134)Online publication date: 16-Nov-2020
https://doi.org/10.1007/978-3-030-63710-1_10
Jankee CVerel SDerbel BFonlupt C(2018)On the Design of a Master-Worker Adaptive Algorithm Selection FrameworkArtificial Evolution10.1007/978-3-319-78133-4_1(1-15)Online publication date: 20-Mar-2018
https://doi.org/10.1007/978-3-319-78133-4_1
Jankee CVerel SDerbel BFlonlupt CEsparcia-Alcázar A(2015)New Adaptive Selection Strategies for Distributed Adaptive Metaheuristic SelectionProceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation10.1145/2739482.2764694(1405-1406)Online publication date: 11-Jul-2015
https://dl.acm.org/doi/10.1145/2739482.2764694
Jankee CVerel SDerbel BFonlupt C(2015)Distributed Adaptive Metaheuristic SelectionRevised Selected Papers of the 12th International Conference on Artificial Evolution - Volume 955410.1007/978-3-319-31471-6_7(83-96)Online publication date: 26-Oct-2015
https://dl.acm.org/doi/10.1007/978-3-319-31471-6_7
Goëffon ALardeux F(2012)Autonomous Local Search Algorithms with Island RepresentationRevised Selected Papers of the 6th International Conference on Learning and Intelligent Optimization - Volume 721910.5555/2961491.2961526(390-395)Online publication date: 16-Jan-2012
https://dl.acm.org/doi/10.5555/2961491.2961526
Candan CGoeffon ALardeux FSaubion FMoore J(2012)A dynamic island model for adaptive operator selectionProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330337(1253-1260)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330163.2330337
Goëffon ALardeux F(2012)Autonomous Local Search Algorithms with Island RepresentationLearning and Intelligent Optimization10.1007/978-3-642-34413-8_33(390-395)Online publication date: 2012
https://doi.org/10.1007/978-3-642-34413-8_33
Goëffon ALardeux F(2011)Optimal One-Max Strategy with Dynamic Island ModelsProceedings of the 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence10.1109/ICTAI.2011.79(485-488)Online publication date: 7-Nov-2011
https://dl.acm.org/doi/10.1109/ICTAI.2011.79

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