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Proceedings Paper

Herd male genetic algorithm
Author(s): H. John Caulfield
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Paper Abstract

There are two extremes in optimization with little ground between them. They are local optimization and global optimization. Local optimization is normally very fast, but the optimum it finds may be far from the best (global) optimum. Global optimization is very slow, but it gives the best optimum- at least in principle. Using mammal herds as rough models, we suggest a new evolutionary method that has aspects of both and achieves intermediate results most of the time: faster-than-global convergence with better-than- local performance.

Paper Details

Date Published: 29 November 2000
PDF: 4 pages
Proc. SPIE 4114, Photonic Devices and Algorithms for Computing II, (29 November 2000); doi: 10.1117/12.408565
Show Author Affiliations
H. John Caulfield, Physical Optics Corp. and Fisk Univ. (United States)

Published in SPIE Proceedings Vol. 4114:
Photonic Devices and Algorithms for Computing II
Khan M. Iftekharuddin; Abdul Ahad Sami Awwal, Editor(s)

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