An Evolutionary Strategy for Surrogate-Based Multiobjective Optimization

Result code in IS VaVaI

RIV/67985807:_____/12:00384786 - isvavai.cz

Result on the web

http://dx.doi.org/10.1109/CEC.2012.6256450

DOI - Digital Object Identifier

10.1109/CEC.2012.6256450

Result language

angličtina

Original language name

An Evolutionary Strategy for Surrogate-Based Multiobjective Optimization

Original language description

The paper presents a surrogate-based evolutionary strategy for multiobjective optimization. The evolutionary strategy uses distance based aggregate surrogate models in two ways: as a part of memetic search and as way to pre-select individuals in order toavoid evaluation of bad individuals. The model predicts the distance of individuals to the currently known Pareto set. The newly proposed algorithm is compared to other algorithms which use similar surrogate models on a set of benchmark functions.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

—

Project

GAP202/11/1368: Learning of functional relationships from high-dimensional data

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2012

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

CEC 2012. Proceedings of IEEE Congress on Evolutionary Computation

ISBN

978-1-4673-1509-8

ISSN

—

e-ISSN

—

Number of pages

7

Pages from-to

1-7

Publisher name

IEEE

Place of publication

Piscataway

Event location

Brisbane

Event date

Jun 10, 2012

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000312859302012