Real-coded adaptive range genetic algorithm applied to transonic wing optimization

Akira Oyama; Shigeru Obayashi; Takashi Nakamura

doi:10.1016/S1568-4946(01)00017-5

Real-coded adaptive range genetic algorithm applied to transonic wing optimization

Akira Oyama, Shigeru Obayashi, Takashi Nakamura

Creative Flow Research Division

Research output: Contribution to journal › Article › peer-review

66 Citations (Scopus)

Abstract

Real-coded adaptive range genetic algorithm (ARGA) has been applied to a practical three-dimensional shape optimization for aerodynamic design of an aircraft wing. The real-coded ARGA possesses both advantages of the binary-coded ARGA and the floating-point representation to overcome the problems of having a large search space that requires continuous sampling. The results confirm that the real-coded ARGA consistently finds better solutions than the conventional real-coded genetic algorithms do.

Original language	English
Pages (from-to)	179-187
Number of pages	9
Journal	Applied Soft Computing
Volume	1
Issue number	3
DOIs	https://doi.org/10.1016/S1568-4946(01)00017-5
Publication status	Published - 2001

Keywords

Computational fluid dynamics
Dynamic coding
Floating-point representation
Genetic algorithm
Parallelization
Real-world application
Wing design

ASJC Scopus subject areas

Software

Access to Document

10.1016/S1568-4946(01)00017-5

Cite this

@article{b56df28459a24ea0b2db89d93f944db0,

title = "Real-coded adaptive range genetic algorithm applied to transonic wing optimization",

abstract = "Real-coded adaptive range genetic algorithm (ARGA) has been applied to a practical three-dimensional shape optimization for aerodynamic design of an aircraft wing. The real-coded ARGA possesses both advantages of the binary-coded ARGA and the floating-point representation to overcome the problems of having a large search space that requires continuous sampling. The results confirm that the real-coded ARGA consistently finds better solutions than the conventional real-coded genetic algorithms do.",

keywords = "Computational fluid dynamics, Dynamic coding, Floating-point representation, Genetic algorithm, Parallelization, Real-world application, Wing design",

author = "Akira Oyama and Shigeru Obayashi and Takashi Nakamura",

year = "2001",

doi = "10.1016/S1568-4946(01)00017-5",

language = "English",

volume = "1",

pages = "179--187",

journal = "Applied Soft Computing Journal",

issn = "1568-4946",

publisher = "Elsevier BV",

number = "3",

}

TY - JOUR

T1 - Real-coded adaptive range genetic algorithm applied to transonic wing optimization

AU - Oyama, Akira

AU - Obayashi, Shigeru

AU - Nakamura, Takashi

PY - 2001

Y1 - 2001

N2 - Real-coded adaptive range genetic algorithm (ARGA) has been applied to a practical three-dimensional shape optimization for aerodynamic design of an aircraft wing. The real-coded ARGA possesses both advantages of the binary-coded ARGA and the floating-point representation to overcome the problems of having a large search space that requires continuous sampling. The results confirm that the real-coded ARGA consistently finds better solutions than the conventional real-coded genetic algorithms do.

AB - Real-coded adaptive range genetic algorithm (ARGA) has been applied to a practical three-dimensional shape optimization for aerodynamic design of an aircraft wing. The real-coded ARGA possesses both advantages of the binary-coded ARGA and the floating-point representation to overcome the problems of having a large search space that requires continuous sampling. The results confirm that the real-coded ARGA consistently finds better solutions than the conventional real-coded genetic algorithms do.

KW - Computational fluid dynamics

KW - Dynamic coding

KW - Floating-point representation

KW - Genetic algorithm

KW - Parallelization

KW - Real-world application

KW - Wing design

UR - http://www.scopus.com/inward/record.url?scp=0012356312&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0012356312&partnerID=8YFLogxK

U2 - 10.1016/S1568-4946(01)00017-5

DO - 10.1016/S1568-4946(01)00017-5

M3 - Article

AN - SCOPUS:0012356312

VL - 1

SP - 179

EP - 187

JO - Applied Soft Computing Journal

JF - Applied Soft Computing Journal

SN - 1568-4946

IS - 3

ER -

Real-coded adaptive range genetic algorithm applied to transonic wing optimization

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this