An improved grey wolf optimization algorithm with multiple tunnels for updating

The grey wolf optimization (GWO) algorithm was proposed in 2014 and after several years of applications, it was used worldwide and all over the subjects which involved computation. Various improvements have been raised to increase the capability of optimization. Based on the best performance of the...

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Vydáno v:Journal of physics. Conference series Ročník 1678; číslo 1; s. 12096 - 12101
Hlavní autoři: Zhao, Juan, Gao, Zheng-Ming
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bristol IOP Publishing 01.11.2020
Témata:
Algorithms
Optimization
Physics
Tunnels
ISSN:1742-6588, 1742-6596
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Abstract The grey wolf optimization (GWO) algorithm was proposed in 2014 and after several years of applications, it was used worldwide and all over the subjects which involved computation. Various improvements have been raised to increase the capability of optimization. Based on the best performance of the slimd mould (SM) algorithm in optimization, a hybridization of the SM and GWO algorithms was proposed about the updating equations, and the GWO algorithm with multiple tunnels for individuals to update their positions during iterations was revised. Simulation experiments were carried out and comparisons were made between the GWO algorithm with variable weights and our proposed new one. Better performance were confirmed and reported as conclusions.
AbstractList The grey wolf optimization (GWO) algorithm was proposed in 2014 and after several years of applications, it was used worldwide and all over the subjects which involved computation. Various improvements have been raised to increase the capability of optimization. Based on the best performance of the slimd mould (SM) algorithm in optimization, a hybridization of the SM and GWO algorithms was proposed about the updating equations, and the GWO algorithm with multiple tunnels for individuals to update their positions during iterations was revised. Simulation experiments were carried out and comparisons were made between the GWO algorithm with variable weights and our proposed new one. Better performance were confirmed and reported as conclusions.
Author Zhao, Juan
Gao, Zheng-Ming
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  givenname: Zheng-Ming
  surname: Gao
  fullname: Gao, Zheng-Ming
  organization: School of computer engineering, Jingchu University of technology , China
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crossref_primary_10_1155_2021_8487997
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10.1016/J.FUTURE.2020.03.055
10.1016/j.ENERGY.2016.05.105
10.1504/IJMMNO.2013.055204
10.1155/2019/2981282
10.1016/J.SWEVO.2015.10.004
10.1016/J.KNOSYS.2019.01.018
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Jayabarathi (JPCS_1678_1_012096bib3) 2016; 111
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SubjectTerms Algorithms
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Physics
Tunnels
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