Research Repository

Distributed evolutionary algorithms and their models: A survey of the state-of-the-art

Gong, Yue-Jiao and Chen, Wei-Neng and Zhan, Zhi-Hui and Zhang, Jun and Li, Yun and Zhang, Qingfu and Li, Jing-Jing (2015) 'Distributed evolutionary algorithms and their models: A survey of the state-of-the-art.' Applied Soft Computing, 34. pp. 286-300. ISSN 1568-4946

1-s2.0-S1568494615002987-main.pdf - Accepted Version

Download (2MB) | Preview


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 parallelize 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.

Item Type: Article
Uncontrolled Keywords: Distributed evolutionary computation; Coevolutionary computation; Evolutionary algorithms; Global optimization; Multiobjective optimization
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 18 May 2015 14:25
Last Modified: 15 Jan 2022 00:45

Actions (login required)

View Item View Item