Title :
SGA Implementation Using Integer Arrays for Storage of Binary Strings
Author :
Kanchan, Pradeep ; D´Souza, Rio
Author_Institution :
Dept. of Comput. Sci. & Eng., St.Joseph Eng. Coll., Vamanjoor, India
Abstract :
The Simple Genetic Algorithm evaluates a group of binary strings on the basis of their fitness, performs crossover and mutation on them and tries to generate a group having maximum fitness. The usual method used for implementing the SGA is by using character arrays for storage of binary strings. But, this method has some disadvantages. The SGA implementation can be termed a success if the average fitness of the new generation is more than the initial average fitness. In this paper, we plan to implement the SGA using integer arrays for storage of binary strings. Then, we plan to compare the initial average fitness with the final average fitness so that the working of SGA can be verified. We have written the application such that varying population sizes can be given to check the correctness of the SGA algorithm.
Keywords :
genetic algorithms; string matching; SGA implementation; binary strings storage; character arrays; initial average fitness; integer arrays; maximum fitness; simple genetic algorithm; Biological cells; Computer science; Educational institutions; Genetic algorithms; Genetic engineering; Genetic mutations; Machine learning; Performance evaluation; Probability; binary string; crossover; fitness function; mutation;
Conference_Titel :
Machine Learning and Computing (ICMLC), 2010 Second International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4244-6006-9
Electronic_ISBN :
978-1-4244-6007-6
DOI :
10.1109/ICMLC.2010.62