Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
479273 | European Journal of Operational Research | 2007 | 16 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Parag C. Pendharkar, Gary J. Koehler,