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Title:
Population size reduction for the differential evolution algorithm
Authors:
ID
Brest, Janez
(
Author
)
ID
Sepesy Maučec, Mirjam
(
Author
)
Files:
http://www.springerlink.com/content/k173214714252683/fulltext.pdf
Language:
English
Work type:
Unknown
Typology:
1.01 - Original Scientific Article
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
This paper studies the efficiency of a recently defined population-based direct global optimization method called Differential Evolution with self-adaptive control parameters. The original version uses fixed population size but a method for gradually reducing population size is proposed in this paper. It improves the efficiency and robustness of the algorithm and can be applied to any variant of a Differential Evolution algorithm. The proposed modification is tested on commonly used benchmark problems for unconstrained optimization and compared with other optimization methods such as Evolutionary Algorithms and Evolution Strategies.
Keywords:
differential evolution
,
control parameter
,
fitness function
,
global function optimization
,
self-adaptation
,
population size
Year of publishing:
2008
PID:
20.500.12556/DKUM-27391
UDC:
004.8
ISSN on article:
0924-669X
COBISS.SI-ID:
11642646
NUK URN:
URN:SI:UM:DK:RPL9QBBL
Publication date in DKUM:
01.06.2012
Views:
2829
Downloads:
139
Metadata:
Categories:
Misc.
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Record is a part of a journal
Title:
Applied intelligence
Shortened title:
Appl. intell.
Publisher:
Kluwer Academic Publishers
ISSN:
0924-669X
COBISS.SI-ID:
2822183
Secondary language
Language:
English
Keywords:
diferencialna evolucija
,
evolucijski algoritmi
,
optimizacijske metode
,
umetna inteligenca
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