GENETIC ALGORITHMS, FLOATING POINT NUMBERS AND APPLICATIONS

Yorick Hardy, Willi-Hans Steeb () and Ruedi Stoop
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Yorick Hardy: International School for Scientific Computing, University of Johannesburg, P. O. Box 524, Auckland Park 2006, South Africa
Willi-Hans Steeb: International School for Scientific Computing, University of Johannesburg, P. O. Box 524, Auckland Park 2006, South Africa
Ruedi Stoop: Institut für Neuroinformatics, ETHZ/UNIZH, Winterthurerstr. 190, 8057 Zürich, Switzerland

International Journal of Modern Physics C (IJMPC), 2005, vol. 16, issue 11, 1811-1816

Abstract: The core in most genetic algorithms is the bitwise manipulations of bit strings. We show that one can directly manipulate the bits in floating point numbers. This means the main bitwise operations in genetic algorithm mutations and crossings are directly done inside the floating point number. Thus the interval under consideration does not need to be known in advance. For applications, we consider the roots of polynomials and finding solutions of linear equations.

Keywords: Genetic algorithms; crossing; mutation; floating point numbers (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1142/S0129183105008321

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