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Multi-population Techniques in Nature Inspired Optimization Algorithms: A Comprehensive Survey

journal contribution
posted on 2018-04-27, 08:39 authored by Haiping Ma, Shigen Shen, Mei Yu, Zhile Yang, Minrui Fei, Huiyu Zhou
Multi-population based nature-inspired optimization algorithms have attracted wide research interests in the last decade, and become one of the frequently used methods to handle real-world optimization problems. Considering the importance and value of multi-population methods and its applications, we believe it is the right time to provide a comprehensive survey of the published work, and also to discuss several aspects for the future research. The purpose of this paper is to summarize the published techniques related to the multi-population methods in nature-inspired optimization algorithms. Beginning with the concept of multi-population optimization, we review basic and important issues in the multi-population methods and discuss their applications in science and engineering. Finally, this paper presents several interesting open problems with future research directions for multi-population optimization methods.

History

Citation

Swarm and Evolutionary Computation, 2018, in press

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Informatics

Version

  • AM (Accepted Manuscript)

Published in

Swarm and Evolutionary Computation

Publisher

Elsevier

issn

2210-6502

eissn

2210-6510

Acceptance date

2018-04-21

Copyright date

2018

Publisher version

https://www.sciencedirect.com/science/article/pii/S2210650217306363

Notes

The file associated with this record is under embargo until 24 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

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