research-article

SofEA: a pool-based framework for evolutionary algorithms using CouchDB

Authors:

Juan J. Merelo,

Carlos M. Fernandes,

Antonio M. Mora,

Anna I. EsparciaAuthors Info & Claims

GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

Pages 109 - 116

https://doi.org/10.1145/2330784.2330802

Published: 07 July 2012 Publication History

Abstract

This paper studies SofEA, an architecture for distributing evolutionary algorithms (EAs) across computer networks in an asynchronous and decentralized way. SofEA is based on a pool architecture which is implemented using an object store interacting asynchronously with several clients. The fact that each client is autonomous leads to a complex behavior that will be examined in this paper, so that the design can be validated, rules of thumb can be extracted and the limits of scalability found. We will show how, beyond the usual measures employed in EA, specific measures such as the number of conflicts across clients can give us hints on the algorithm behavior, and how implementation details can change not only the running time, but also the behavior of the evolutionary algorithm itself. By using these measures we try to find ideal values for parameters such as the simultaneous number of individuals evaluated by a client or the way these are chosen from the pool.

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Cited By

Abdul Halim ADas SIsmail IAbdul Halim ADas SIsmail I(2025)Location, Size, and CapacityInto a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control10.1007/978-3-031-75577-4_1(1-152)Online publication date: 18-Jan-2025
https://doi.org/10.1007/978-3-031-75577-4_1
García-Valdez MMancilla ACastillo OMerelo-Guervós J(2023)Distributed and Asynchronous Population-Based Optimization Applied to the Optimal Design of Fuzzy ControllersSymmetry10.3390/sym1502046715:2(467)Online publication date: 9-Feb-2023
https://doi.org/10.3390/sym15020467
Khalloof HJakob WShahoud SDuepmeier CHagenmeyer V(2020)A Generic Scalable Method for Scheduling Distributed Energy Resources Using Parallelized Population-Based MetaheuristicsProceedings of the Future Technologies Conference (FTC) 2020, Volume 210.1007/978-3-030-63089-8_1(1-21)Online publication date: 1-Nov-2020
https://doi.org/10.1007/978-3-030-63089-8_1
Show More Cited By

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SofEA: a pool-based framework for evolutionary algorithms using CouchDB

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cover image ACM Conferences

GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

July 2012

1586 pages

ISBN:9781450311786

DOI:10.1145/2330784

Editor:
Terence Soule
University of Idaho, USA
,
General Chair:
Jason H. Moore
Dartmouth College, USA

Copyright © 2012 ACM.

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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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

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Published: 07 July 2012

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GECCO '12

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SIGEVO

GECCO '12: Genetic and Evolutionary Computation Conference

July 7 - 11, 2012

Pennsylvania, Philadelphia, USA

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

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Cited By

Abdul Halim ADas SIsmail IAbdul Halim ADas SIsmail I(2025)Location, Size, and CapacityInto a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control10.1007/978-3-031-75577-4_1(1-152)Online publication date: 18-Jan-2025
https://doi.org/10.1007/978-3-031-75577-4_1
García-Valdez MMancilla ACastillo OMerelo-Guervós J(2023)Distributed and Asynchronous Population-Based Optimization Applied to the Optimal Design of Fuzzy ControllersSymmetry10.3390/sym1502046715:2(467)Online publication date: 9-Feb-2023
https://doi.org/10.3390/sym15020467
Khalloof HJakob WShahoud SDuepmeier CHagenmeyer V(2020)A Generic Scalable Method for Scheduling Distributed Energy Resources Using Parallelized Population-Based MetaheuristicsProceedings of the Future Technologies Conference (FTC) 2020, Volume 210.1007/978-3-030-63089-8_1(1-21)Online publication date: 1-Nov-2020
https://doi.org/10.1007/978-3-030-63089-8_1
Salza PHemberg EFerrucci FO'Reilly U(2017)Towards evolutionary machine learning comparison, competition, and collaboration with a multi-cloud platformProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3067695.3082474(1263-1270)Online publication date: 15-Jul-2017
https://dl.acm.org/doi/10.1145/3067695.3082474
García-Valdez MTrujillo LMerelo JFernández de Vega FOlague G(2014)The EvoSpace Model for Pool-Based Evolutionary AlgorithmsJournal of Grid Computing10.1007/s10723-014-9319-213:3(329-349)Online publication date: 7-Nov-2014
https://doi.org/10.1007/s10723-014-9319-2

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