We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Genetic Algorithm: A Search of Complex Spaces

by Namita Khurana, Anju Rathi, Akshatha.P.S
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 25 - Number 7
Year of Publication: 2011
Authors: Namita Khurana, Anju Rathi, Akshatha.P.S
10.5120/3045-4136

Namita Khurana, Anju Rathi, Akshatha.P.S . Genetic Algorithm: A Search of Complex Spaces. International Journal of Computer Applications. 25, 7 ( July 2011), 13-17. DOI=10.5120/3045-4136

@article{ 10.5120/3045-4136,
author = { Namita Khurana, Anju Rathi, Akshatha.P.S },
title = { Genetic Algorithm: A Search of Complex Spaces },
journal = { International Journal of Computer Applications },
issue_date = { July 2011 },
volume = { 25 },
number = { 7 },
month = { July },
year = { 2011 },
issn = { 0975-8887 },
pages = { 13-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume25/number7/3045-4136/ },
doi = { 10.5120/3045-4136 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:11:07.369352+05:30
%A Namita Khurana
%A Anju Rathi
%A Akshatha.P.S
%T Genetic Algorithm: A Search of Complex Spaces
%J International Journal of Computer Applications
%@ 0975-8887
%V 25
%N 7
%P 13-17
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Living species solve very complex problem of optimization through the mechanism of evolution and natural selection. Genetic Algorithm has been a field of active interest and applied to solve problems almost in all the fields like Computer Science, Electrical Engg., Mechanical Engg., Optimization, Biology and Image Processing etc. One important application of Genetic Algorithm is to search complex spaces and function optimization. A genetic algorithm begins its search with random solution of the problem. The initial population is evolved to new population using Genetic operators like reproduction, crossover and mutation. A Genetic Algorithm keeps evolving the successive populations unless some criterion is met or a reasonable acceptable solution is found. In this paper Genetic Algorithm has been applied to schwefel function to find the best fit chromosome so far.

References
  1. D.E.Goldberg, “Genetic Algorithms in search, Optimization and Machine Learning”, Addison Wesley Publishing Company, Ind. U.S.A, 1989.
  2. Charles C.Peck, Atam P. Dhawan, “Genetic algorithm as global random search methods: An alternative Perspective”, Evolutionary Computation, Volume 3 Issue1, MIT Press, march 1995.
  3. Wolfram MathWorld available at http://mathworld.com.
  4. Pratibha Bajpai et al./Indian Journal of Computer Science and Engineering Vol 1 No 3 199-206, “ Genetic Algorithm-an Approach to solve Global Optimization Problems”.
  5. http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page2530.htm
  6. Melanie Mitche,”An introduction to genetic Algorithm”, MIT press,1998.
  7. L.T.Leng, Guided Genetic Algorithm, Doctoral Dissertation.University of Essex, 1999.
  8. Yashwant Kanitkar “Pointers in c”.
  9. Lawrence Davis. Handbook of Genetic Alogorithms. Van Nostrand Reinhold, NewYork, 1991.
  10. D. Whitley, D.Garrett, and J.Watson. Genetic Quad Search.
  11. MathWorks available at www.mathworks.com
  12. Wikipedia (2004).Genetic Algorithm. Available from URL: http://en.wikipedia.org/wiki/Genetic_algorithm
  13. Holland, J. (1975). Adaptation In Natural and Artificial Systems. University of Michigan Press, Ann Arbor.
  14. Schaffer, J.D. and Eshelman, L. (1993). Real-coded genetic algorithms and interval schemata. Foundations of Genetic Algorithms,2,ed.D.Whitley.Morgan Kaufmann, an Mateo, A.
  15. Schwefel, H.P. (1981). Numerical optimization of Computer models. John Wiley, New York.
  16. Baker, J. (1985). Adaptive selection methods for genetic algorithms. In proceedings of the International Conference on Genetic Algorithms and Their Applications.
  17. L.T.Leng,Guided genetic algorithm,Doctrol Dissertation. University of Essex,1999.
  18. L. Painton, J.Campbell, “Genetic Algorithms in optimization of system Reliability” Reliability, IEEE Transaction on Volume: 44 ,Issue 2, Digital Object Identifier.
  19. T.Weise, “Global Optimization Algorithms-Theory and Application”.
Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm Schwefel function Crossover Mutation Selection

Powered by PhDFocusTM