Promoting diversity using migration strategies in
distributed genetic algorithms
D. Power, C. Ryan, and R. Azad. Proceedings of the 2005 IEEE Congress on Evolutionary
Computation, 2, page 1831--1838. Edinburgh, Scotland, UK, IEEE Press, (2-5 September 2005)
DOI: doi:10.1109/CEC.2005.1554910
Abstract
This paper presents a new migration strategy that
improves the overall quality of solutions in a
distributed genetic algorithm (DGA) involving a number
of concurrently evolving populations. The idea behind
this improvement is to incorporate a diversity guided
selection mechanism that selects a diverse set of
individuals for migration from the evolving
populations. To accompany this selection mechanism an
alternative replacement policy which replaces
individuals that have more than one of their copies
present in the population (clones) is also
investigated. This increases diversity within a
population and reduces premature convergence. Results
show that it leads to a better performance when
compared with the send-best-replace-worst strategy.
%0 Conference Paper
%1 Power:Pdu:cec2005
%A Power, David
%A Ryan, Conor
%A Azad, R. Muhammad Atif
%B Proceedings of the 2005 IEEE Congress on Evolutionary
Computation
%C Edinburgh, Scotland, UK
%D 2005
%E Corne, David
%E Michalewicz, Zbigniew
%E McKay, Bob
%E Eiben, Gusz
%E Fogel, David
%E Fonseca, Carlos
%E Greenwood, Garrison
%E Raidl, Gunther
%E Tan, Kay Chen
%E Zalzala, Ali
%I IEEE Press
%K Algorithms, Genetic algorithms, alternative clones, concurrently distributed diversity evolving genetic guided migration parallel policy, populations, replacement selection, strategy,
%P 1831--1838
%R doi:10.1109/CEC.2005.1554910
%T Promoting diversity using migration strategies in
distributed genetic algorithms
%U http://ieeexplore.ieee.org/iel5/10417/33080/01554910.pdf?tp=&isnumber=33080&arnumber=1554910&punumber=10417
%V 2
%X This paper presents a new migration strategy that
improves the overall quality of solutions in a
distributed genetic algorithm (DGA) involving a number
of concurrently evolving populations. The idea behind
this improvement is to incorporate a diversity guided
selection mechanism that selects a diverse set of
individuals for migration from the evolving
populations. To accompany this selection mechanism an
alternative replacement policy which replaces
individuals that have more than one of their copies
present in the population (clones) is also
investigated. This increases diversity within a
population and reduces premature convergence. Results
show that it leads to a better performance when
compared with the send-best-replace-worst strategy.
%@ 0-7803-9363-5
@inproceedings{Power:Pdu:cec2005,
abstract = {This paper presents a new migration strategy that
improves the overall quality of solutions in a
distributed genetic algorithm (DGA) involving a number
of concurrently evolving populations. The idea behind
this improvement is to incorporate a diversity guided
selection mechanism that selects a diverse set of
individuals for migration from the evolving
populations. To accompany this selection mechanism an
alternative replacement policy which replaces
individuals that have more than one of their copies
present in the population (clones) is also
investigated. This increases diversity within a
population and reduces premature convergence. Results
show that it leads to a better performance when
compared with the send-best-replace-worst strategy.},
added-at = {2008-06-19T17:46:40.000+0200},
address = {Edinburgh, Scotland, UK},
author = {Power, David and Ryan, Conor and Azad, R. Muhammad Atif},
biburl = {https://www.bibsonomy.org/bibtex/28d2ce940229d3e51171495a014014e18/brazovayeye},
booktitle = {Proceedings of the 2005 IEEE Congress on Evolutionary
Computation},
doi = {doi:10.1109/CEC.2005.1554910},
editor = {Corne, David and Michalewicz, Zbigniew and McKay, Bob and Eiben, Gusz and Fogel, David and Fonseca, Carlos and Greenwood, Garrison and Raidl, Gunther and Tan, Kay Chen and Zalzala, Ali},
interhash = {9ee37de9299481df391d9ca492e96fd6},
intrahash = {8d2ce940229d3e51171495a014014e18},
isbn = {0-7803-9363-5},
keywords = {Algorithms, Genetic algorithms, alternative clones, concurrently distributed diversity evolving genetic guided migration parallel policy, populations, replacement selection, strategy,},
month = {2-5 September},
pages = {1831--1838},
publisher = {IEEE Press},
timestamp = {2008-06-19T17:49:52.000+0200},
title = {Promoting diversity using migration strategies in
distributed genetic algorithms},
url = {http://ieeexplore.ieee.org/iel5/10417/33080/01554910.pdf?tp=&isnumber=33080&arnumber=1554910&punumber=10417},
volume = 2,
year = 2005
}