Output details
11 - Computer Science and Informatics
Middlesex University
Article title
A quickly convergent continuous ant colony optimization algorithm with Scout Ants
Type
D - Journal article
Title of journal
Applied Mathematics and Computation
Article number
-
Volume number
218
Issue number
5
First page of article
1805
ISSN of journal
00963003
Year of publication
2011
Number of additional authors
2
Additional information
<22>Ant Colony Optimization (ACO) is an active research topic in Genetic Algorithms. Many existing variants of ACO algorithms suffer either optimization inaccuracy or slow speed. This paper proposed, for the first time, a novel collaborative approach between scout and foraging ants to search for a global optimal solution to function optimization problems. The numerical experiments show that the new method has a much better optimization accuracy, and is up to one hundred times faster in simulation speed than almost all existing variants of ACO algorithms. This work was funded by the grants from the China National Science Foundation.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
0
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
