Volume 2, Issue 2, September 2015, Pages 131 - 134
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
- 10.2991/jrnal.2015.2.2.14How to use a DOI?
- 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 Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Yifei Du AU - QinLian Ma AU - Kenji Aoki AU - Makoto Sakamoto AU - Hiroshi Furutani AU - Yu-an Zhang PY - 2015 DA - 2015/09/01 TI - Hitting Time Analysis of OneMax Problem in Genetic Algorithm JO - Journal of Robotics, Networking and Artificial Life SP - 131 EP - 134 VL - 2 IS - 2 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.2015.2.2.14 DO - 10.2991/jrnal.2015.2.2.14 ID - Du2015 ER -