Theoretical and Experimental Study of Crossover Operators of Genetic Algorithms

N. P. Belfiore and A. Esposito
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N. P. Belfiore: University of Rome
A. Esposito: University of Rome

Journal of Optimization Theory and Applications, 1998, vol. 99, issue 2, No 1, 302 pages

Abstract: Abstract This paper is concerned with crossover operators for genetic algorithms (GAs) which are used to solve problems based on real numbers. First, a classification of the operators is introduced, dividing crossover into a vector-level and a variable-level operator. The theoretical study of variable-level operators for binary coded GAs leads to the discovery of two properties, which are used to define certain characteristics of crossover operators used by real-number encoded GAs. For variable-level operators, the experimental distributions of the offspring variables of given pairs of parent variables are then found. Finally, an experimental comparison of crossover operator performance is carried out.

Keywords: Genetic algorithms; real-number based problems; binary encoding; real-number encoding; crossover operators; convergence (search for similar items in EconPapers)
Date: 1998
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Citations: View citations in EconPapers (1)

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DOI: 10.1023/A:1021766025497

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