Fuzzy Coding of Genetic Algorithms

George Irwin; Sanjay Sharma

doi:10.1109/TEVC.2003.812217

Fuzzy Coding of Genetic Algorithms

George Irwin, Sanjay Sharma

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

42 Citations (Scopus)

Abstract

A well-cited paper suggesting fuzzy coding as an alternative to the conventional binary, grey and floating-point representations used in genetic algorithms.

Original language	English
Pages (from-to)	344-355
Number of pages	12
Journal	IEEE Transactions on Evolutionary Computation
Volume	7(4)
Issue number	4
DOIs	https://doi.org/10.1109/TEVC.2003.812217
Publication status	Published - Aug 2003

ASJC Scopus subject areas

Control and Systems Engineering
Artificial Intelligence
Theoretical Computer Science
Computational Theory and Mathematics
Safety, Risk, Reliability and Quality

Access to Document

10.1109/TEVC.2003.812217

Link to publication in Scopus

Fingerprint Dive into the research topics of 'Fuzzy Coding of Genetic Algorithms'. Together they form a unique fingerprint.

Cite this

@article{80d7343cf3b14a6f965a3c9ec2d61d74,

title = "Fuzzy Coding of Genetic Algorithms",

abstract = "A well-cited paper suggesting fuzzy coding as an alternative to the conventional binary, grey and floating-point representations used in genetic algorithms.",

author = "George Irwin and Sanjay Sharma",

year = "2003",

month = aug,

doi = "10.1109/TEVC.2003.812217",

language = "English",

volume = "7(4)",

pages = "344--355",

journal = "IEEE Transactions on Evolutionary Computation",

issn = "1089-778X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "4",

}

TY - JOUR

T1 - Fuzzy Coding of Genetic Algorithms

AU - Irwin, George

AU - Sharma, Sanjay

PY - 2003/8

Y1 - 2003/8

N2 - A well-cited paper suggesting fuzzy coding as an alternative to the conventional binary, grey and floating-point representations used in genetic algorithms.

AB - A well-cited paper suggesting fuzzy coding as an alternative to the conventional binary, grey and floating-point representations used in genetic algorithms.

UR - http://www.scopus.com/inward/record.url?scp=0042863353&partnerID=8YFLogxK

U2 - 10.1109/TEVC.2003.812217

DO - 10.1109/TEVC.2003.812217

M3 - Article

VL - 7(4)

SP - 344

EP - 355

JO - IEEE Transactions on Evolutionary Computation

JF - IEEE Transactions on Evolutionary Computation

SN - 1089-778X

IS - 4

ER -