Rodyti trumpą aprašą

dc.contributor.authorFilatovas, Ernestas
dc.contributor.authorKurasova, Olga
dc.contributor.authorRedondo, Juana López
dc.contributor.authorFernández, José
dc.date.accessioned2023-09-18T16:42:37Z
dc.date.available2023-09-18T16:42:37Z
dc.date.issued2016
dc.identifier.other(BIS)VGT02-000032539
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/116225
dc.description.abstractMulti-objective preference-based evolutionary algorithms approximate the part of the Pareto front that meets the preference information expressed by the Decision Maker. However, only a few of such algorithms are able to obtain well-distributed solutions covering the complete “region of interest”. In this work a preference-based evolutionary algorithm for approximating the region of interest of multi-objective optimization problems is proposed. The efficiency of the proposed algorithm has been experimentally evaluated and compared to another state-of-the-art multi-objective preference- based evolutionary algorithm by solving a set of multi-objective optimization benchmark problems.eng
dc.format.extentp. 21-24
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.subjectFM03 - Fizinių, technologinių ir ekonominių procesų matematiniai modeliai ir metodai / Mathematical models and methods of physical, technological and economic processes
dc.titleA preference-based multi-objective evolutionary algorithm for approximating a region of interest
dc.typeKonferencijos pranešimo santrauka / Conference presentation abstract
dcterms.references13
dc.type.pubtypeT2 - Konferencijos pranešimo tezės / Conference presentation abstract
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionVilniaus universitetas
dc.contributor.institutionUniversity of Almería
dc.contributor.institutionUniversity of Murcia
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enMulti-objective optimization
dc.subject.enEvolutionary algorithms
dc.subject.enPreference-based algorithms
dcterms.sourcetitleGOW’16 : proceedings of the XIII Global Optimization Workshop, 4-8 September 2016 : [extended abstracts]
dc.publisher.nameUniversity of Minho
dc.publisher.cityBraga, Portugal
dc.identifier.elaba18300855


Šio įrašo failai

FailaiDydisFormatasPeržiūra

Su šiuo įrašu susijusių failų nėra.

Šis įrašas yra šioje (-se) kolekcijoje (-ose)

Rodyti trumpą aprašą