Authors
Yifei Du, QinLian Ma, Kenji Aoki, Makoto Sakamoto, Hiroshi Furutani, Yu-an
Zhang
Corresponding Author
Yifei Du
Available Online 1 September 2015.
DOI
https://doi.org/10.2991/jrnal.2015.2.2.14
Keywords
genetic algorithms, OneMax problem, Markov model, convergence time, hitting
time
Abstract
Genetic algorithms (GAs) are stochastic optimization techniques, and we
have studied the effects of stochastic fluctuation in the process of GA
evolution. A mathematical study was carried out for GA on OneMax function
within the framework of Markov chain model. We treated the task of estimating
convergence time of the Markov chain for OneMax problem. Then, in order
to study hitting time, we study the state after convergence.
Copyright
© 2013, the Authors. Published by
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).