Hybrid evolutionary multi-objective optimization with enhanced convergence and diversity

Sindhya, Karthik

dc.contributor.author	Sindhya, Karthik
dc.date.accessioned	2011-09-12T09:38:10Z
dc.date.available	2011-09-12T09:38:10Z
dc.date.issued	2011
dc.identifier.isbn	978-951-39-4414-8
dc.identifier.other	oai:jykdok.linneanet.fi:1182925
dc.identifier.uri	https://jyx.jyu.fi/handle/123456789/36669
dc.format.extent	64 sivua
dc.language.iso	eng
dc.publisher	University of Jyväskylä
dc.relation.ispartofseries	Jyväskylä studies in computing
dc.relation.isversionof	ISBN 978-951-39-4372-1
dc.rights	In Copyright
dc.subject.other	hybridialgoritmit
dc.subject.other	evoluutioalgoritmit
dc.subject.other	PIE
dc.subject.other	monitavoiteoptimointi
dc.subject.other	hybrid framework
dc.subject.other	multiple criteria decision making
dc.subject.other	interactive evolutionary multi-objective optimization
dc.subject.other	mutation
dc.subject.other	NSGA-II
dc.subject.other	differential evolution
dc.subject.other	achievement scalarizing function
dc.subject.other	NAUTILUS method
dc.title	Hybrid evolutionary multi-objective optimization with enhanced convergence and diversity
dc.type	Diss.
dc.identifier.urn	URN:ISBN:978-951-39-4414-8
dc.type.dcmitype	Text	en
dc.type.ontasot	Väitöskirja	fi
dc.type.ontasot	Doctoral dissertation	en
dc.contributor.tiedekunta	Informaatioteknologian tiedekunta	fi
dc.contributor.tiedekunta	Faculty of Information Technology	en
dc.contributor.yliopisto	University of Jyväskylä	en
dc.contributor.yliopisto	Jyväskylän yliopisto	fi
dc.contributor.oppiaine	Tietotekniikka	fi
dc.relation.issn	1456-5390
dc.relation.numberinseries	131
dc.rights.accesslevel	openAccess
dc.subject.yso	muuttujat
dc.subject.yso	Pareto-optimit
dc.subject.yso	EMO-algoritmit
dc.rights.url	https://rightsstatements.org/page/InC/1.0/

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A New Hybrid Mutation Operator for Multiobjective Optimization with Differential Evolution

Sindhya, Karthik; Ruuska, Sauli; Haanpää, Tomi; Miettinen, Kaisa (Springer, 2011)

Differential evolution has become one of the most widely used evolution- ary algorithms in multiobjective optimization. Its linear mutation operator is a sim- ple and powerful mechanism to generate trial vectors. However, ...
A Performance Indicator for Interactive Evolutionary Multiobjective Optimization Methods

Aghaei Pour, Pouya; Bandaru, Sunith; Afsar, Bekir; Emmerich, Michael; Miettinen, Kaisa (IEEE, 2024)

In recent years, interactive evolutionary multiobjective optimization methods have been getting more and more attention. In these methods, a decision maker, who is a domain expert, is iteratively involved in the solution ...
DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization

Misitano, Giovanni; Saini, Bhupinder Singh; Afsar, Bekir; Shavazipour, Babooshka; Miettinen Kaisa (Institute of Electrical and Electronics Engineers (IEEE), 2021)

Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the ...
Desirable properties of performance indicators for assessing interactive evolutionary multiobjective optimization methods

Aghaei Pour, Pouya; Bandaru, Sunith; Afsar, Bekir; Miettinen, Kaisa (ACM, 2022)

Interactive methods support decision makers in finding the most preferred solution in multiobjective optimization problems. They iteratively incorporate the decision maker's preference information to find the best balance ...
E-NAUTILUS: A decision support system for complex multiobjective optimization problems based on the NAUTILUS method

Ruiz, Ana B.; Sindhya, Karthik; Miettinen, Kaisa; Ruiz, Francisco; Luque, Mariano (Elsevier BV * North-Holland; Association of European Operational Research Societies, 2015)

Interactive multiobjective optimization methods cannot necessarily be easily used when (industrial) multiobjective optimization problems are involved. There are at least two important factors to be considered with any ...

Hybrid evolutionary multi-objective optimization with enhanced convergence and diversity

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Aineisto kuuluu seuraaviin kokoelmiin

Samankaltainen aineisto

A New Hybrid Mutation Operator for Multiobjective Optimization with Differential Evolution ﻿

A Performance Indicator for Interactive Evolutionary Multiobjective Optimization Methods ﻿

DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization ﻿

Desirable properties of performance indicators for assessing interactive evolutionary multiobjective optimization methods ﻿

E-NAUTILUS: A decision support system for complex multiobjective optimization problems based on the NAUTILUS method ﻿

A New Hybrid Mutation Operator for Multiobjective Optimization with Differential Evolution

A Performance Indicator for Interactive Evolutionary Multiobjective Optimization Methods

DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization

Desirable properties of performance indicators for assessing interactive evolutionary multiobjective optimization methods

E-NAUTILUS: A decision support system for complex multiobjective optimization problems based on the NAUTILUS method