Lorentz JANTSCHI, Sorana D. BOLBOACA and Radu E. SESTRAS (2010) Classical Approaches of Genetic Algorithms and their Suitability

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Classical Approaches of Genetic Algorithms and their Suitability

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CONTRIBUTORS:

	Author:	Lorentz JANTSCHI (Technical University of Cluj-Napoca)
	Author:	Sorana D. BOLBOACA (Iuliu Hatieganu University of Medicine and Pharmacy Cluj-Napoca)
	Author:	Radu E. SESTRAS (University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca, Romania)

JOURNAL:

Asian journal of chemistry, 22(3), 2275 - 2284.

YEAR:

2010

PUB TYPE:

Journal Article

SUBJECT(S):

chemistry - biochemistry; chemistry - computational; chemistry - inorganic; informatics - simulation

DISCIPLINE:

Chemistry

HTTP:

http://lori.academicdirect.org/works/?f=234

LANGUAGE:

English

PUB ID:

103-483-578 (Last edited on 2011/01/31 03:15:36 US/Mountain)

SPONSOR(S):

ABSTRACT:
Genetic algorithms derived from observations of nature and simulation of artificial selection of organisms with multiple loci that control a measurable trait. To date, genetic algorithms evolved into complex and strong informatics tools able to deal with hard problems of decision, classification, optimization and simulation. A series of studies reported biotechnology hard problems solved using genetic algorithms. In this context, the aim of the present article is to introduce genetic algorithms and to present their suitability for biotechnology hard problems. Important results are reported in the available literature that deal with the application of genetic algorithms for biotechnology process modelling.

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