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Tackling Real-Coded Genetic Algorithms

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Tackling Real-Coded Genetic Algorithms

M. Nishidhar Babu | Y. Kiran | A. Ramesh | V. Rajendra


M. Nishidhar Babu | Y. Kiran | A. Ramesh | V. Rajendra "Tackling Real-Coded Genetic Algorithms" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1, December 2017, pp.217-223, URL: https://www.ijtsrd.com/papers/ijtsrd5905.pdf

Genetic algorithms play a significant role, as search techniques for handling complex spaces, in many fields such as artificial intelligence, engineering, robotic, etc. Genetic algorithms are based on the underlying genetic process in biological organisms and on the natural evolution principles of populations. These algorithms process a population of chromosomes, which represent search space solutions, with three operations: selection, crossover and mutation.Under its initial formulation, the search space solutions are coded using the binary alphabet. However, the good properties related with these algorithms do not stem from the use of this alphabet; other coding types have been considered for the representation issue, such as real coding, which would seem particularly natural when tackling optimization problems of parameters with variables in continuous domains. In this paper we review the features of real-coded genetic algorithms. Different models of genetic operators and some mechanisms available for studying the behavior of this type of genetic algorithms are revised and compared.

Genetic algorithms, real coded genetic algorithm

Volume-2 | Issue-1, December 2017
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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