•  Home
  • Library
  • DRO home
Submit research Contact DRO

DRO

An information entropy-based evolutionary computation for multi-factorial optimization

Lim, TY, Tan, CJ, Wong, WP and Lim, Chee Peng 2022, An information entropy-based evolutionary computation for multi-factorial optimization, Applied Soft Computing, vol. 114, pp. 1-25, doi: 10.1016/j.asoc.2021.108071.

Attached Files
Name Description MIMEType Size Downloads

Title An information entropy-based evolutionary computation for multi-factorial optimization
Author(s) Lim, TY
Tan, CJ
Wong, WP
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Journal name Applied Soft Computing
Volume number 114
Article ID ARTN 108071
Start page 1
End page 25
Total pages 25
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2022-01
ISSN 1568-4946
1872-9681
Keyword(s) Computer Science
Computer Science, Artificial Intelligence
Computer Science, Interdisciplinary Applications
DIFFERENTIAL EVOLUTION
GREY WOLF OPTIMIZER
Multi-factorial optimization
MULTITASKING
MUTATION
Parameter control
Science & Technology
SEARCH ALGORITHM
Simulated binary crossover
STRATEGY
Technology
TIME
Language eng
DOI 10.1016/j.asoc.2021.108071
Field of Research 0102 Applied Mathematics
0801 Artificial Intelligence and Image Processing
0806 Information Systems
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30161458

Document type: Journal Article
Collection: Institute for Intelligent Systems Research and Innovation (IISRI)
Related Links
Link Description
Connect to published version
Go to link with your DU access privileges
 
Connect to Elements publication management system
Go to link with your DU access privileges
 
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 3 times in TR Web of Science
Scopus Citation Count Cited 3 times in Scopus Google Scholar Search Google Scholar
Access Statistics: 6 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Fri, 14 Jan 2022, 14:04:23 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.