Hitting Time Analysis of OneMax Problem in Genetic Algorithm

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/).

Download article (PDF)