Number of the records: 1

Combining Multiobjective and Single-Objective Genetic Algorithms in Heterogeneous Island Model

SYSNO ASEP	0358846
Document Type	C - Proceedings Paper (int. conf.)
R&D Document Type	Conference Paper
Title	Combining Multiobjective and Single-Objective Genetic Algorithms in Heterogeneous Island Model
Author(s)	Pilát, M. (CZ) Neruda, Roman (UIVT-O)_{SAI, RID, ORCID}
Source Title	CEC 2010. Proceedings of the IEEE Congress on Evolutionary Computation. - Piscataway : IEEE, 2010 - ISBN 978-1-4244-6910-9
Pages	s. 1-8
Number of pages	8 s.
Action	WCCI 2010. IEEE World Congress on Computational Intelligence
Event date	18.07.2010-23.07.2010
VEvent location	Barcelona
Country	ES - Spain
Event type	WRD
Language	eng - English
Country	US - United States
Keywords	multiobjective optimization ; single-objective optimization ; genetic algorithms ; island model ; hybrid model
Subject RIV	IN - Informatics, Computer Science
R&D Projects	OC10047 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
CEZ	AV0Z10300504 - UIVT-O (2005-2011)
UT WOS	000287375801047
EID SCOPUS	79959408739
DOI	10.1109/CEC.2010.5586075
Annotation	The majority of multiobjective genetic algorithms is computationally expensive, therefore they often need to be parallelized before they can be used to solve practical tasks. Parallelization of multiobjective genetic algorithms is a relatively studied area, but no clearly winning approach has appeared yet. In this paper we present a novel parallel hybrid algorithm which combines multiobjective and single-objective genetic algorithms. We how that this algorithm can be successfully used to solve multiobjective optimization problems while outperforming more traditional parallel versions of multiobjective genetic algorithms.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2012

Number of the records: 1