Article (Scientific journals)
A novel meta-heuristic algorithm: dynamic virtual bats algorithm
TOPAL, Ali Osman; Altun, Oguz
2016In Information Sciences, 354, p. 222-235
Peer Reviewed verified by ORBi
 

Files


Full Text
topal2016.pdf
Publisher postprint (836.71 kB)
Request a copy

All documents in ORBilu are protected by a user license.

Send to



Details



Keywords :
Dynamic Virtual Bats Algorithm; Bio-inspired computation; Global numerical optimization; Nature-inspired algorithms
Abstract :
[en] Nature-inspired algorithms are a very important part of meta-heuristics. A novel nature inspired algorithm called the Dynamic Virtual Bats Algorithm (DVBA) is presented in this paper. DVBA is inspired by a bat’s ability to manipulate frequency and wavelength of the emitted sound waves when hunting. A role based search has been developed to improve the diversification and intensification capability of Bat Algorithm. In the DVBA, there are only two bats: explorer and exploiter bat. While the explorer bat explores the search space, the exploiter bat makes an intensive search of the local with the highest probability of locating the desired target. Depending on their location, bats exchange the roles dynamically. The performance of the DVBA is extensively evaluated on a suite of 30 bound-constrained optimization problems from CEC 2014 and compared favorably with other well-known meta-heuristics algorithms. The experimental results demonstrated that the proposed DVBA outperform, or is comparable to, its competitors in terms of the quality of final solution and its convergence rates.
Disciplines :
Computer science
Author, co-author :
TOPAL, Ali Osman ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Altun, Oguz;  Yildiz Technical University > Computer Engineering
External co-authors :
yes
Language :
English
Title :
A novel meta-heuristic algorithm: dynamic virtual bats algorithm
Publication date :
22 March 2016
Journal title :
Information Sciences
ISSN :
0020-0255
eISSN :
1872-6291
Publisher :
Elsevier
Volume :
354
Pages :
222-235
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Computational Sciences
Available on ORBilu :
since 02 May 2023

Statistics


Number of views
37 (1 by Unilu)
Number of downloads
0 (0 by Unilu)

OpenCitations
 
59
OpenAlex citations
 
80
WoS citations
 
61

publications
0
supporting
0
mentioning
0
contrasting
0
Smart Citations
0
0
0
0
Citing PublicationsSupportingMentioningContrasting
View Citations

See how this article has been cited at scite.ai

scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

Bibliography


Similar publications



Contact ORBilu