research-article

Injecting CMA-ES into MOEA/D

Authors:

Saúl Zapotecas-Martínez,

Arnaud Liefooghe,

Dimo Brockhoff,

Hernán E. Aguirre,

Kiyoshi TanakaAuthors Info & Claims

GECCO '15: Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation

Pages 783 - 790

https://doi.org/10.1145/2739480.2754754

Published: 11 July 2015 Publication History

Abstract

MOEA/D is an aggregation-based evolutionary algorithm which has been proved extremely efficient and effective for solving multi-objective optimization problems. It is based on the idea of decomposing the original multi-objective problem into several single-objective subproblems by means of well-defined scalarizing functions. Those single-objective subproblems are solved in a cooperative manner by defining a neighborhood relation between them. This makes MOEA/D particularly interesting when attempting to plug and to leverage single-objective optimizers in a multi-objective setting. In this context, we investigate the benefits that MOEA/D can achieve when coupled with CMA-ES, which is believed to be a powerful single-objective optimizer. We rely on the ability of CMA-ES to deal with injected solutions in order to update different covariance matrices with respect to each subproblem defined in MOEA/D. We show that by cooperatively evolving neighboring CMA-ES components, we are able to obtain competitive results for different multi-objective benchmark functions.

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Cited By

Lu CLiu YZhang Q(2024)MOEA/D-CMA Made Better with (l+l)-CMA-ES2024 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC60901.2024.10612007(1-8)Online publication date: 30-Jun-2024
https://doi.org/10.1109/CEC60901.2024.10612007
Sato TWatanabe K(2024)A topology optimization of on-chip planar inductor based on evolutional on/off method and CMA-ESCOMPEL - The international journal for computation and mathematics in electrical and electronic engineering10.1108/COMPEL-10-2023-050343:4(920-931)Online publication date: 2-Apr-2024
https://doi.org/10.1108/COMPEL-10-2023-0503
Yao XFeng ZZhang LNiu WYang TXiao YTang H(2024)Multi-objective cooperation search algorithm based on decomposition for complex engineering optimization and reservoir operation problemsApplied Soft Computing10.1016/j.asoc.2024.112442167(112442)Online publication date: Dec-2024
https://doi.org/10.1016/j.asoc.2024.112442
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Index Terms

Injecting CMA-ES into MOEA/D
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
    2. Search methodologies
2. Theory of computation
  1. Design and analysis of algorithms
    1. Algorithm design techniques
      1. Dynamic programming

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Published In

cover image ACM Conferences

GECCO '15: Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation

July 2015

1496 pages

ISBN:9781450334723

DOI:10.1145/2739480

Editor:
Sara Silva
Universidade de Lisboa, Portugal
,
General Chair:
Anna I. Esparcia-Alcázar
Universitat Politècnica de València, Spain

Copyright © 2015 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

Publication History

Published: 11 July 2015

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GECCO '15

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SIGEVO

GECCO '15: Genetic and Evolutionary Computation Conference

July 11 - 15, 2015

Madrid, Spain

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GECCO '15 Paper Acceptance Rate 182 of 505 submissions, 36%;

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

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Cited By

Lu CLiu YZhang Q(2024)MOEA/D-CMA Made Better with (l+l)-CMA-ES2024 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC60901.2024.10612007(1-8)Online publication date: 30-Jun-2024
https://doi.org/10.1109/CEC60901.2024.10612007
Sato TWatanabe K(2024)A topology optimization of on-chip planar inductor based on evolutional on/off method and CMA-ESCOMPEL - The international journal for computation and mathematics in electrical and electronic engineering10.1108/COMPEL-10-2023-050343:4(920-931)Online publication date: 2-Apr-2024
https://doi.org/10.1108/COMPEL-10-2023-0503
Yao XFeng ZZhang LNiu WYang TXiao YTang H(2024)Multi-objective cooperation search algorithm based on decomposition for complex engineering optimization and reservoir operation problemsApplied Soft Computing10.1016/j.asoc.2024.112442167(112442)Online publication date: Dec-2024
https://doi.org/10.1016/j.asoc.2024.112442
Han JWatanabe S(2023)A New Hyper-Heuristic Multi-Objective Optimisation Approach Based on MOEA/D FrameworkBiomimetics10.3390/biomimetics80705218:7(521)Online publication date: 2-Nov-2023
https://doi.org/10.3390/biomimetics8070521
Wu XChen CDing S(2021)A Modified MOEA/D Algorithm for Solving Bi-Objective Multi-Stage Weapon-Target Assignment ProblemIEEE Access10.1109/ACCESS.2021.30791529(71832-71848)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3079152
Xiang YYang XZhou YHuang H(2020)Enhancing Decomposition-Based Algorithms by Estimation of Distribution for Constrained Optimal Software Product SelectionIEEE Transactions on Evolutionary Computation10.1109/TEVC.2019.292241924:2(245-259)Online publication date: Apr-2020
https://doi.org/10.1109/TEVC.2019.2922419
Omran SEl-Behaidy WYoussif A(2020)Decomposition Based Multi-objectives Evolutionary Algorithms Challenges and CircumventionIntelligent Computing10.1007/978-3-030-52246-9_6(82-93)Online publication date: 4-Jul-2020
https://doi.org/10.1007/978-3-030-52246-9_6
Miyamoto MWatanabe S(2019)A New Approach to Generate Solutions Combining Crossover and Estimation of Distribution Operators for EMO Algorithm2019 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI44817.2019.9002866(2088-2095)Online publication date: Dec-2019
https://doi.org/10.1109/SSCI44817.2019.9002866
Zhou AZhao HZhang HZhang G(2019)Pareto Optimal Set Approximation by Models: A Linear CaseEvolutionary Multi-Criterion Optimization10.1007/978-3-030-12598-1_36(451-462)Online publication date: 3-Feb-2019
https://doi.org/10.1007/978-3-030-12598-1_36
Zangari MConstantino ACeberio J(2018)A decomposition-based kernel of Mallows models algorithm for bi- and tri-objective permutation flowshop scheduling problemApplied Soft Computing10.1016/j.asoc.2018.07.01171(526-537)Online publication date: Oct-2018
https://doi.org/10.1016/j.asoc.2018.07.011
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