Stability analysis of the particle dynamics in bat algorithm: standard and modified versions

Stability and convergence analysis have been previously accomplished for some population-based search and swarm intelligence algorithms like Particle Swarm Optimization and Gravitational Search Algorithm. However, there is no adequate theoretical analysis for Bat Algorithm (BA) in the literature. Th...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Engineering with computers Ročník 37; číslo 4; s. 2865 - 2876
Hlavní autoři: Fozuni Shirjini, Mahsa, Nikanjam, Amin, Aliyari Shoorehdeli, Mahdi
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Springer London 01.10.2021
Springer Nature B.V
Témata:
ISSN:0177-0667, 1435-5663
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Stability and convergence analysis have been previously accomplished for some population-based search and swarm intelligence algorithms like Particle Swarm Optimization and Gravitational Search Algorithm. However, there is no adequate theoretical analysis for Bat Algorithm (BA) in the literature. The BA is a type of optimization algorithms which is inspired by the motion of small bats searching for hunting their preys. In this study, stability and convergence of the particle dynamics in the standard version BA are analyzed, and some restrictions are described. Then, new updating relations have been proposed. Also the dynamics of the algorithm have been investigated, and sufficient conditions for stability have been derived using Lyapunov stability analysis. Extensive simulation is used to examine the findings. The results confirm the theoretical predictions and indicate the stability and convergence of the proposed updating relations.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0177-0667
1435-5663
DOI:10.1007/s00366-020-00979-z