research-article

A new memetic strategy for the numerical treatment of multi-objective optimization problems

Authors:

Oliver Schuetze,

Gustavo Sanchez,

Carlos A. Coello CoelloAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 705 - 712

https://doi.org/10.1145/1389095.1389232

Published: 12 July 2008 Publication History

Abstract

In this paper we propose a novel iterative search procedure for multi-objective optimization problems. The iteration process -- though derivative free -- utilizes the geometry of the directional cones of such optimization problems, and is capable both of moving toward and along the (local) Pareto set depending on the distance of the current iterate toward this set. Next, we give one possible way of integrating this local search procedure into a given EMO algorithm resulting in a novel memetic strategy. Finally, we present some numerical results on some well-known benchmark problems indicating the strength of both the local search strategy as well as the new hybrid approach.

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https://dl.acm.org/doi/10.1016/j.eswa.2024.124641
Lin QLin WZhu ZGong MLi JCoello C(2021)Multimodal Multiobjective Evolutionary Optimization With Dual Clustering in Decision and Objective SpacesIEEE Transactions on Evolutionary Computation10.1109/TEVC.2020.300882225:1(130-144)Online publication date: Feb-2021
https://doi.org/10.1109/TEVC.2020.3008822
Li FDong SLiu YShang Z(2021) An IGD + Performance Indicator Based Particle Swarm Optimizer For Multi-objective Optimization 2021 33rd Chinese Control and Decision Conference (CCDC)10.1109/CCDC52312.2021.9601927(3633-3638)Online publication date: 22-May-2021
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A new memetic strategy for the numerical treatment of multi-objective optimization problems

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cover image ACM Conferences

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Copyright © 2008 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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Published: 12 July 2008

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July 12 - 16, 2008

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

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Cited By

Gao XSong S(2024)A switching competitive swarm optimizer for multi-objective optimization with irregular Pareto frontsExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.124641255:PBOnline publication date: 18-Oct-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.124641
Lin QLin WZhu ZGong MLi JCoello C(2021)Multimodal Multiobjective Evolutionary Optimization With Dual Clustering in Decision and Objective SpacesIEEE Transactions on Evolutionary Computation10.1109/TEVC.2020.300882225:1(130-144)Online publication date: Feb-2021
https://doi.org/10.1109/TEVC.2020.3008822
Li FDong SLiu YShang Z(2021) An IGD + Performance Indicator Based Particle Swarm Optimizer For Multi-objective Optimization 2021 33rd Chinese Control and Decision Conference (CCDC)10.1109/CCDC52312.2021.9601927(3633-3638)Online publication date: 22-May-2021
https://doi.org/10.1109/CCDC52312.2021.9601927
Grimme CKerschke PTrautmann H(2019)Multimodality in Multi-objective Optimization – More Boon than Bane?Evolutionary Multi-Criterion Optimization10.1007/978-3-030-12598-1_11(126-138)Online publication date: 3-Feb-2019
https://doi.org/10.1007/978-3-030-12598-1_11
Moscato PCotta C(2018)An Accelerated Introduction to Memetic AlgorithmsHandbook of Metaheuristics10.1007/978-3-319-91086-4_9(275-309)Online publication date: 21-Sep-2018
https://doi.org/10.1007/978-3-319-91086-4_9
Vasile MRicciardi L(2016)Multi Agent Collaborative SearchNEO 201510.1007/978-3-319-44003-3_10(223-252)Online publication date: 24-Aug-2016
https://doi.org/10.1007/978-3-319-44003-3_10
Cotta CGallardo JMathieson LMoscato P(2016)Memetic Algorithms: A Contemporary IntroductionWiley Encyclopedia of Electrical and Electronics Engineering10.1002/047134608X.W8330(1-15)Online publication date: 15-Nov-2016
https://doi.org/10.1002/047134608X.W8330
Parisi SPirotta MSmacchia NBascetta LRestelli M(2014)Policy gradient approaches for multi-objective sequential decision making2014 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN.2014.6889738(2323-2330)Online publication date: Jul-2014
https://doi.org/10.1109/IJCNN.2014.6889738
Jiao LWang HShang RLiu F(2013)A co-evolutionary multi-objective optimization algorithm based on direction vectorsInformation Sciences: an International Journal10.1016/j.ins.2012.12.013228(90-112)Online publication date: 1-Apr-2013
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Zuiani FVasile M(2013)Multi Agent Collaborative Search based on Tchebycheff decompositionComputational Optimization and Applications10.1007/s10589-013-9552-956:1(189-208)Online publication date: 1-Sep-2013
https://dl.acm.org/doi/10.1007/s10589-013-9552-9
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