16 December 1992 Provably convergent inhomogeneous genetic annealing algorithm
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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.
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Griff L. Bilbro, Jue Hall, Lawrence A. Ray, "Provably convergent inhomogeneous genetic annealing algorithm", Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130816; https://doi.org/10.1117/12.130816
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