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A Novel Distributed Quantum-Behaved Particle Swarm Optimization
Joint Authors
Xue, Yu
Li, Yangyang
Chen, Zhenghan
Wang, Yang
Jiao, Licheng
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-03
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Quantum-behaved particle swarm optimization (QPSO) is an improved version of particle swarm optimization (PSO) and has shown superior performance on many optimization problems.
But for now, it may not always satisfy the situations.
Nowadays, problems become larger and more complex, and most serial optimization algorithms cannot deal with the problem or need plenty of computing cost.
Fortunately, as an effective model in dealing with problems with big data which need huge computation, MapReduce has been widely used in many areas.
In this paper, we implement QPSO on MapReduce model and propose MapReduce quantum-behaved particle swarm optimization (MRQPSO) which achieves parallel and distributed QPSO.
Comparisons are made between MRQPSO and QPSO on some test problems and nonlinear equation systems.
The results show that MRQPSO could complete computing task with less time.
Meanwhile, from the view of optimization performance, MRQPSO outperforms QPSO in many cases.
American Psychological Association (APA)
Li, Yangyang& Chen, Zhenghan& Wang, Yang& Jiao, Licheng& Xue, Yu. 2017. A Novel Distributed Quantum-Behaved Particle Swarm Optimization. Journal of Optimization،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1185915
Modern Language Association (MLA)
Li, Yangyang…[et al.]. A Novel Distributed Quantum-Behaved Particle Swarm Optimization. Journal of Optimization No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1185915
American Medical Association (AMA)
Li, Yangyang& Chen, Zhenghan& Wang, Yang& Jiao, Licheng& Xue, Yu. A Novel Distributed Quantum-Behaved Particle Swarm Optimization. Journal of Optimization. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1185915
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1185915