Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance
A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer...
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| Published in | Journal of Applied Mathematics Vol. 2017; no. 2017; pp. 1 - 15-005 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Cairo, Egypt
Hindawi Limiteds
2017
Hindawi Publishing Corporation Hindawi John Wiley & Sons, Inc Wiley |
| Subjects | |
| Online Access | Get full text |
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| Abstract | A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer to produce both variants’ strength. Some unimodal, multimodal, and fixed-dimension multimodal test functions are used to check the solution quality and performance of HPSOGWO variant. The numerical and statistical solutions show that the hybrid variant outperforms significantly the PSO and GWO variants in terms of solution quality, solution stability, convergence speed, and ability to find the global optimum. |
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| AbstractList | A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer to produce both variants' strength. Some unimodal, multimodal, and fixeddimension multimodal test functions are used to check the solution quality and performance of HPSOGWO variant. The numerical and statistical solutions show that the hybrid variant outperforms significantly the PSO and GWO variants in terms of solution quality, solution stability, convergence speed, and ability to find the global optimum. A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer to produce both variants’ strength. Some unimodal, multimodal, and fixed-dimension multimodal test functions are used to check the solution quality and performance of HPSOGWO variant. The numerical and statistical solutions show that the hybrid variant outperforms significantly the PSO and GWO variants in terms of solution quality, solution stability, convergence speed, and ability to find the global optimum. |
| Audience | Academic |
| Author | Singh, Narinder Singh, S. B. |
| Author_xml | – sequence: 1 fullname: Singh, Narinder – sequence: 2 fullname: Singh, S. B. |
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| Cites_doi | 10.1109/jsee.2015.00037 10.1080/15325008.2015.1041625 10.1007/978-3-319-13572-4_1 10.1155/2014/215472 10.1007/978-3-319-23207-2_25 10.1016/j.neucom.2015.06.083 10.1007/s12293-017-0234-5 10.1142/S1469026817500122 10.1016/j.jocs.2015.03.011 10.1016/j.ins.2009.03.004 10.1155/2008/316145 10.1016/j.amc.2006.07.025 10.1002/cplx.21601 10.1109/4235.585893 10.1155/2016/7950348 10.1007/s00521-015-1934-8 10.1016/j.advengsoft.2013.12.007 10.1023/A:1016540724870 |
| ContentType | Journal Article |
| Copyright | Copyright © 2017 Narinder Singh and S. B. Singh. COPYRIGHT 2017 John Wiley & Sons, Inc. Copyright © 2017 Narinder Singh and S. B. Singh.; This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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| Snippet | A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO).... |
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| SubjectTerms | Algorithms Civil engineering Convergence Convergence (Mathematics) Exploitation Genetic algorithms International conferences Mathematical optimization Mathematical research Optimization techniques Particle swarm optimization Quality Wolves |
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| Title | Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance |
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| Volume | 2017 |
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