Comparison of genetic algorithm and quantum genetic algorithm
Joint Authors
Chikhi, Salim
Laboudi, Zakariyya
Source
The International Arab Journal of Information Technology
Issue
Vol. 9, Issue 3 (31 May. 2012), pp.243-249, 7 p.
Publisher
Publication Date
2012-05-31
Country of Publication
Jordan
No. of Pages
7
Main Subjects
Topics
Abstract EN
Evolving solutions rather than computing them certainly represents a promising programming approach.
Evolutionary computation has already been known in computer science since more than 4 decades.
More recently, another alternative of evolutionary algorithms was invented : Quantum Genetic Algorithms (QGA).
In this paper, we outline the approach of QGA by giving a comparison with Conventional Genetic Algorithm (CGA).
Our results have shown that QGA can be a very promising tool for exploring search spaces.
American Psychological Association (APA)
Laboudi, Zakariyya& Chikhi, Salim. 2012. Comparison of genetic algorithm and quantum genetic algorithm. The International Arab Journal of Information Technology،Vol. 9, no. 3, pp.243-249.
https://search.emarefa.net/detail/BIM-305252
Modern Language Association (MLA)
Laboudi, Zakariyya& Chikhi, Salim. Comparison of genetic algorithm and quantum genetic algorithm. The International Arab Journal of Information Technology Vol. 9, no. 3 (May. 2012), pp.243-249.
https://search.emarefa.net/detail/BIM-305252
American Medical Association (AMA)
Laboudi, Zakariyya& Chikhi, Salim. Comparison of genetic algorithm and quantum genetic algorithm. The International Arab Journal of Information Technology. 2012. Vol. 9, no. 3, pp.243-249.
https://search.emarefa.net/detail/BIM-305252
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 248
Record ID
BIM-305252
