Journal of Robotics, Networking and Artificial Life

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/).

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
2 - 2
Pages
131 - 134
Publication Date
2015/09/01
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
10.2991/jrnal.2015.2.2.14How to use a DOI?
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  -