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Proceedings Paper

Global convergence of genetic algorithms
Author(s): Gunar E. Liepins
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Paper Abstract

We extend an approach to global convergence for genetic algorithms via a homogeneous Markov chain argument that does not depend on mutation. Our result is a proof of convergence to a set of populations which contain the optimal.

Paper Details

Date Published: 16 December 1992
PDF: 5 pages
Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130817
Show Author Affiliations
Gunar E. Liepins, Oak Ridge National Lab. (United States)


Published in SPIE Proceedings Vol. 1766:
Neural and Stochastic Methods in Image and Signal Processing
Su-Shing Chen, Editor(s)

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