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An Application of Preference-Inspired Co-Evolutionary Algorithm to Sectorization

2022Journal article Restricted access
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dc.contributor.authorOzturk, E. Goksu
dc.contributor.authorRocha, Pedro
dc.contributor.authorSousa, Filipe
dc.contributor.authorLima, Maria Margarida
dc.contributor.authorRodrigues, Ana Maria
dc.contributor.authorSoeiro Ferreira, José
dc.contributor.authorCatarina Nunes, Ana
dc.contributor.authorLopes, Isabel Cristina
dc.contributor.authorOliveira, Cristina
dc.date.accessioned2023-01-27T08:25:24Z
dc.date.available2023-01-27T08:25:24Z
dc.date.issued2022
dc.description.abstractSectorization problems have significant challenges arising from the many objectives that must be optimised simultaneously. Several methods exist to deal with these many-objective optimisation problems, but each has its limitations. This paper analyses an application of Preference Inspired Co-Evolutionary Algorithms, with goal vectors (PICEA-g) to sectorization problems. The method is tested on instances of different size difficulty levels and various configurations for mutation rate and population number. The main purpose is to find the best configuration for PICEA-g to solve sectorization problems. Performancemetrics are used to evaluate these configurations regarding the solutions’ spread, convergence, and diversity in the solution space. Several test trials showed that big and medium-sized instances perform better with low mutation rates and large population sizes. The opposite is valid for the small size instances.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/978-3-031-09385-2_23pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/21923
dc.language.isoengpt_PT
dc.relationPOCI-01-0145-FEDER-031671pt_PT
dc.relationCenter of Organizational and Social Studies of Polytechnic of Porto
dc.subjectSectorization Problemspt_PT
dc.subjectCo-evolutionary algorithmspt_PT
dc.subjectMany objectives optimizationpt_PT
dc.titleAn Application of Preference-Inspired Co-Evolutionary Algorithm to Sectorizationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCenter of Organizational and Social Studies of Polytechnic of Porto
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05422%2F2020/PT
oaire.citation.endPage268pt_PT
oaire.citation.startPage257pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameOzturk
person.familyNameSousa
person.familyNameAlmeida Lima
person.familyNameRodrigues
person.familyNameSoeiro Ferreira
person.familyNameNunes
person.familyNameLopes
person.givenNameElif Goksu
person.givenNameFilipe
person.givenNameMaria Margarida
person.givenNameAna Maria
person.givenNameJosé
person.givenNameAna Catarina
person.givenNameIsabel Cristina
person.identifierR-000-837
person.identifier2277025
person.identifier.ciencia-idE815-014D-61C5
person.identifier.ciencia-idD712-912E-CC9B
person.identifier.ciencia-id2B17-0B7B-EAC1
person.identifier.ciencia-idBC14-DF88-AEBC
person.identifier.orcid0000-0002-8407-1871
person.identifier.orcid0000-0001-9349-3454
person.identifier.orcid0000-0003-2231-4978
person.identifier.orcid0000-0003-1070-3626
person.identifier.orcid0000-0002-7552-9924
person.identifier.orcid0000-0002-4025-1985
person.identifier.orcid0000-0002-4833-470X
person.identifier.ridA-2148-2013
person.identifier.ridL-7458-2017
person.identifier.scopus-author-id16198890300
person.identifier.scopus-author-id36742403500
person.identifier.scopus-author-id36185835200
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
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