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Proceedings Paper

Provably convergent inhomogeneous genetic annealing algorithm
Author(s): Griff L. Bilbro; Jue Hall; Lawrence A. Ray
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Paper Abstract

We define genetic annealing as simulated annealing applied to a population of several solutions when candidates are generated from more than one (parent) solution at a time. We show that such genetic annealing algorithms can inherit the convergence properties of simulated annealing. We present two examples, one that generates each candidate by crossing pairs of parents and a second that generates each candidate from the entire population. We experimentally apply these two extreme versions of genetic annealing to a problem in vector quantization.

Paper Details

Date Published: 16 December 1992
PDF: 11 pages
Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130816
Show Author Affiliations
Griff L. Bilbro, North Carolina State Univ. (United States)
Jue Hall, North Carolina State Univ. (United States)
Lawrence A. Ray, Eastman Kodak Co. (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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