Genetic Algorithm and its Variants: Theory and Applications

Mishra, Bineet and Patnaik, Rakesh Kumar (2009) Genetic Algorithm and its Variants: Theory and Applications. BTech thesis.



The Genetic Algorithm is a popular optimization technique which is bio-inspired and is based on the concepts of natural genetics and natural selection theories proposed by Charles Darwin. The Algorithm functions on three basic genetic operators of selection, crossover and mutation. Based on the types of these operators GA has many variants like Real coded GA, Binary coded GA, Sawtooth GA, Micro GA, Improved GA, Differential Evolution GA. This paper discusses a few of the forms of GA and applies the techniques to the problem of Function optimization and System Identification. The paper makes a comparative analysis of the advantages and disadvantages of the different types of GA. The computer simulations illustrate the results. It also makes a comparison between the GA technique and Incremental LMS algorithm for System Identification.

Item Type:Thesis (BTech)
Uncontrolled Keywords:Genetic Algorithm, Crossover, Mutation, Selection, Real coded GA, Binary code GA, Sawtooth GA, Differential Evolution GA, Incremental LMS Algorithm, System Identification.
Subjects:Engineering and Technology > Electronics and Communication Engineering > Genetic Algorithm
Divisions: Engineering and Technology > Department of Electronics and Communication Engineering
ID Code:199
Deposited By:Rakesh Kumar Patnaik
Deposited On:10 May 2009 21:11
Last Modified:10 May 2009 21:11
Supervisor(s):Panda, G

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