- author = "Yue-Jiao Gong and Wei-Neng Chen and Zhi-Hui Zhan and Jun Zhang and Yun Li and Qingfu Zhang and Jing-Jing Li",
- title = "Distributed evolutionary algorithms and their models: A survey of the state-of-the-art",
- journal = "Applied Soft Computing",
- year = "2015",
- volume = "34",
- pages = "286--300",
- month = sep,
- keywords = "genetic algorithms, genetic programming, Distributed evolutionary computation, Coevolutionary computation, Evolutionary algorithms, Global optimization, Multiobjective optimization",
- ISSN = "1568-4946",
-
URL = "
http://repository.essex.ac.uk/13796/1/1-s2.0-S1568494615002987-main.pdf",
-
URL = "
https://www.sciencedirect.com/science/article/pii/S1568494615002987",
-
DOI = "
doi:10.1016/j.asoc.2015.04.061",
- size = "15 pages",
- abstract = "The increasing complexity of real-world optimization problems raises new challenges to evolutionary computation. Responding to these challenges, distributed evolutionary computation has received considerable attention over the past decade. This article provides a comprehensive survey of the state-of-the-art distributed evolutionary algorithms and models, which have been classified into two groups according to their task division mechanism. Population-distributed models are presented with master-slave, island, cellular, hierarchical, and pool architectures, which parallelise an evolution task at population, individual, or operation levels. Dimension-distributed models include coevolution and multi-agent models, which focus on dimension reduction. Insights into the models, such as synchronization, homogeneity, communication, topology, speedup, advantages and disadvantages are also presented and discussed. The study of these models helps guide future development of different and/or improved algorithms. Also highlighted are recent hotspots in this area, including the cloud and MapReduce-based implementations, GPU and CUDA-based implementations, distributed evolutionary multiobjective optimization, and real-world applications. Further, a number of future research directions have been discussed, with a conclusion that the development of distributed evolutionary computation will continue to flourish.",
-
notes = "Brief mention of GP
Also known as \cite{GONG2015286}
School of Advanced Computing,Sun Yat-Sen University, Guangzhou, China",
