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.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)