%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 }