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A Survey of Diversity Oriented Optimization: Problems, Indicators, and Algorithms

2017-04-29Capítulo de livro Acesso aberto
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datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg07:Energias Renováveis e Acessíveis
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorBasto-Fernandes, Vitor
dc.contributor.authorYevseyeva, Iryna
dc.contributor.authorDeutz, André
dc.contributor.authorEmmerich, Michael
dc.date.accessioned2026-03-24T10:10:01Z
dc.date.available2026-03-24T10:10:01Z
dc.date.issued2017-04-29
dc.description.abstractIn this chapter it is discussed, how the concept of diversity plays a crucial role in contemporary (multi-objective) optimization algorithms. It is shown that diversity maintenance can have a different purpose, such as improving global convergence reliability or finding alternative solutions to a (multi-objective) optimization problem. Moreover, different algorithms are reviewed that put special emphasis on diversity maintenance, such as multicriteria evolutionary optimization algorithms, multimodal optimization, artificial immune systems, and techniques from set oriented numerics. Diversity maintenance enters in different search operators and is used for different reasons in these algorithms. Among them we highlight evolutionary, swarm-based, artificial immune system-based, and indicator-based approaches to diversity optimization. In order to understand indicator-based approaches, we will review some of the most common diversity indices that can be used to quantitatively assess diversity. Based on the discussion, ’diversity oriented optimization’ is suggested as a term encompassing optimization techniques that adress diversity maintainance as a major ingredient of the search paradigm. To bring order into all these different approaches, an ontology on diversity oriented optimization is proposed. It provides a systematic overview of the various concepts, methods, and applications and it can be extended in the future work.eng
dc.identifier.citationBasto-Fernandes, V., Yevseyeva, I., Deutz, A., Emmerich, M. (2017). A Survey of Diversity Oriented Optimization: Problems, Indicators, and Algorithms. In: Emmerich, M., Deutz, A., Schütze, O., Legrand, P., Tantar, E., Tantar, AA. (eds) EVOLVE – A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII. Studies in Computational Intelligence, vol 662. Springer, Cham. https://doi.org/10.1007/978-3-319-49325-1_1
dc.identifier.doi10.1007/978-3-319-49325-1_1
dc.identifier.isbn9783319493244
dc.identifier.isbn9783319493251
dc.identifier.issn1860-949X
dc.identifier.issn1860-9503
dc.identifier.urihttp://hdl.handle.net/10400.8/15953
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer International Publishing
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-319-49325-1_1
dc.relation.ispartofStudies in Computational Intelligence
dc.relation.ispartofEVOLVE – A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII
dc.rights.uriN/A
dc.titleA Survey of Diversity Oriented Optimization: Problems, Indicators, and Algorithmseng
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage19
oaire.citation.startPage1
oaire.citation.titleEVOLVE – A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameBasto-Fernandes
person.givenNameVitor
person.identifier.ciencia-id581C-52BB-AC4E
person.identifier.orcid0000-0003-4269-5114
person.identifier.ridN-1891-2016
person.identifier.scopus-author-id53363129900
relation.isAuthorOfPublicationfb2d3703-9d6a-4c22-bbc4-9ff14c162feb
relation.isAuthorOfPublication.latestForDiscoveryfb2d3703-9d6a-4c22-bbc4-9ff14c162feb

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