TY - GEN
T1 - A dual dynamic migration policy for island model genetic algorithm
AU - Gozali, Alfian Akbar
AU - Fujimura, Shigeru
N1 - Funding Information:
Indonesia Endowment Fund for Education (LPDP), a scholarship from Ministry of Finance, Republic of Indonesia, supports this work. We conduct this research while at Graduate School of Information, Production, and Systems, Waseda University, Japan.
Funding Information:
Thank you for Indonesia Endowment Fund for Education (LPDP), a scholarship from Ministry of Finance, Republic of Indonesia, for supporting this work.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/2/27
Y1 - 2018/2/27
N2 - The common problem in island model is the way to migrate individual from one to another island, or usually called as migration policy. Previous researches in this movement protocol could be categorized into two different approaches, diversity preservation based such as migration protocol in LIMGA and better island pursuing based such as new dynamic migration policy. The main purpose of this works is to introduce a brand-new migration mechanism called as Dual Dynamic Migration Policy (DDMP) for island model GA. DDMP will take the advantage from result pursuer of dynamic migration policy and convergence avoider of LIMGA's migration protocol. The experiment result shows that DDMP could give great result while carrying out the general optimization cases. It could produce the best score result for all cases among previous island model migration methods. This work also compares DDMP with the-best-known-so-far solution for the problem set.
AB - The common problem in island model is the way to migrate individual from one to another island, or usually called as migration policy. Previous researches in this movement protocol could be categorized into two different approaches, diversity preservation based such as migration protocol in LIMGA and better island pursuing based such as new dynamic migration policy. The main purpose of this works is to introduce a brand-new migration mechanism called as Dual Dynamic Migration Policy (DDMP) for island model GA. DDMP will take the advantage from result pursuer of dynamic migration policy and convergence avoider of LIMGA's migration protocol. The experiment result shows that DDMP could give great result while carrying out the general optimization cases. It could produce the best score result for all cases among previous island model migration methods. This work also compares DDMP with the-best-known-so-far solution for the problem set.
KW - genetic algorithm
KW - island model
KW - migration policy
KW - migration protocol
UR - http://www.scopus.com/inward/record.url?scp=85049305741&partnerID=8YFLogxK
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U2 - 10.1109/SIET.2017.8304117
DO - 10.1109/SIET.2017.8304117
M3 - Conference contribution
AN - SCOPUS:85049305741
T3 - Proceedings - 2017 International Conference on Sustainable Information Engineering and Technology, SIET 2017
SP - 100
EP - 106
BT - Proceedings - 2017 International Conference on Sustainable Information Engineering and Technology, SIET 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Conference on Sustainable Information Engineering and Technology, SIET 2017
Y2 - 24 November 2017 through 25 November 2017
ER -
