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Proceedings Paper

Evaluating alternative forms of crossover in evolutionary computation on linear systems of equations
Author(s): David B. Fogel; Peter J. Angeline
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Paper Abstract

Experiments are conducted to assess the utility of alternative crossover operators within a framework of evolutionary computation. Systems of linear equations are used for testing the efficiency of one-point, two-point, and uniform crossover. The results indicate that uniform crossover, which disrupts building blocks maximally, generates statistically significantly better solutions than one- or two-point crossover. Moreover, for the cases of small population sizes, crossing over existing solutions with completely random solutions can perform as well or better than the traditional one- and two-point operators.

Paper Details

Date Published: 13 October 1998
PDF: 7 pages
Proc. SPIE 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, (13 October 1998); doi: 10.1117/12.326732
Show Author Affiliations
David B. Fogel, Natural Selection, Inc. (United States)
Peter J. Angeline, Natural Selection, Inc. (United States)

Published in SPIE Proceedings Vol. 3455:
Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation
Bruno Bosacchi; David B. Fogel; James C. Bezdek, Editor(s)

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