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The Simple Genetic Algorithm Performance: A Comparative Study on the Operators Combination

Authors:
Delmar Broglio Carvalho
João Carlos Nunes Bittencourt
Thiago D'Martin Maia

Keywords: Genetic Algorithm; Parameterization of GA; Generational Replacement Model; Single-Point Crossover; Uniform Crossover.

Abstract:
This paper presents a comparative and experimental study about the performance of the Simple Genetic Algorithm (SGA) using five classic benchmarking functions. The performance analysis is accomplished on the combination of the operators of reproduction and crossover with the control parameters having been fixed. The overall behavior of the SGA is evaluated by the fitness of the best individual analyzed during the evolution and at the ending of the same one. The results that are presented show that the SGA can be effective and competitive to optimization on a test suite of benchmark functions.

Pages: 20 to 24

Copyright: Copyright (c) IARIA, 2011

Publication date: October 23, 2011

Published in: conference

ISSN: 2308-3484

ISBN: 978-1-61208-161-8

Location: Barcelona, Spain

Dates: from October 23, 2011 to October 29, 2011