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Volume 9, Issue 2
A Survey on Parallel Evolutionary Computing and Introduce Four General Frameworks to Parallelize All EC Algorithms and Create New Operation for Migration

Amin Majd and Golnaz Sahebi

J. Info. Comput. Sci. , 9 (2014), pp. 097-105.

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  • Abstract
Optimization and solving NP-hard problems are very important and Evolutionary Computing (EC) methods are useful and popular. There are different types of EC methods that most of them are sequential and some others have parallel implementation. In first step we want to review some parallel implementation of EC methods and in second step we introduce four general frameworks to parallelize all EC algorithms that they are Master-Slave method, Hybrid method, Simple Multi-population method and Repulsive Multi-Population method. Finally we create a new operation for migration to keep population diversity.
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@Article{JICS-9-097, author = {Amin Majd and Golnaz Sahebi}, title = {A Survey on Parallel Evolutionary Computing and Introduce Four General Frameworks to Parallelize All EC Algorithms and Create New Operation for Migration}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {9}, number = {2}, pages = {097--105}, abstract = { Optimization and solving NP-hard problems are very important and Evolutionary Computing (EC) methods are useful and popular. There are different types of EC methods that most of them are sequential and some others have parallel implementation. In first step we want to review some parallel implementation of EC methods and in second step we introduce four general frameworks to parallelize all EC algorithms that they are Master-Slave method, Hybrid method, Simple Multi-population method and Repulsive Multi-Population method. Finally we create a new operation for migration to keep population diversity. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22586.html} }
TY - JOUR T1 - A Survey on Parallel Evolutionary Computing and Introduce Four General Frameworks to Parallelize All EC Algorithms and Create New Operation for Migration AU - Amin Majd and Golnaz Sahebi JO - Journal of Information and Computing Science VL - 2 SP - 097 EP - 105 PY - 2024 DA - 2024/01 SN - 9 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22586.html KW - parallel genetic algorithms, parallel PSO, parallel ant colony optimization, parallel bee colony optimization, parallel memetic algorithm, repulsive operation. AB - Optimization and solving NP-hard problems are very important and Evolutionary Computing (EC) methods are useful and popular. There are different types of EC methods that most of them are sequential and some others have parallel implementation. In first step we want to review some parallel implementation of EC methods and in second step we introduce four general frameworks to parallelize all EC algorithms that they are Master-Slave method, Hybrid method, Simple Multi-population method and Repulsive Multi-Population method. Finally we create a new operation for migration to keep population diversity.
Amin Majd and Golnaz Sahebi. (2024). A Survey on Parallel Evolutionary Computing and Introduce Four General Frameworks to Parallelize All EC Algorithms and Create New Operation for Migration. Journal of Information and Computing Science. 9 (2). 097-105. doi:
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