Interactive and non-interactive hybrid immigrants schemes for ant algorithms in dynamic environments
Date
2014-09-22
Advisors
Journal Title
Journal ISSN
ISSN
Volume Title
Publisher
IEEE Press
Type
Conference
Peer reviewed
Yes
Abstract
Dynamic optimization problems (DOPs) have been a major challenge for ant colony optimization (ACO) algorithms. The integration of ACO algorithms with immigrants schemes showed promising results on different DOPs. Each type of immigrants scheme aims to address a DOP with specific characteristics. For example, random and elitism-based immigrants perform well on severely and slightly changing environments, respectively. In this paper, two hybrid immigrants, i.e., non-interactive and interactive, schemes are proposed to combine the merits of the aforementioned immigrants schemes. The experiments on a series of dynamic travelling salesman problems showed that the hybridization of immigrants further improves the performance of ACO algorithms.
Description
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
Keywords
Dynamic optimization problems, ant colony optimization, hybrid immigrants
Citation
Mavrovouniotis, M. and Yang, S. (2014) Interactive and non-interactive hybrid immigrants schemes for ant algorithms in dynamic environments. Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China, July 2014. pp. 1542-1549.