General steady state distribution based stopping criteria for finite length genetic algorithms

General steady state distribution based stopping criteria for finite length genetic algorithms

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Article ID: iaor20084670
Country: Netherlands
Volume: 176
Issue: 3
Start Page Number: 1436
End Page Number: 1451
Publication Date: Feb 2007
Journal: European Journal of Operational Research
Authors: ,
Keywords: markov processes
Abstract:

We propose two general stopping criteria for finite length, simple genetic algorithms based on steady state distributions, and empirically investigate the impact of mutation rate, string length, crossover rate and population size on their convergence. Our first stopping criterion is based on the second largest eigenvalue of the genetic algorithm transition matrix, and the second stopping criterion is based on minorization conditions.

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