Elitism-based immigrants for ant colony optimization in dynamic environments: Adapting the replacement rate

Date

2014-09-22

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

IEEE Press

Type

Conference

Peer reviewed

Yes

Abstract

The integration of immigrants schemes with ant colony optimization (ACO) algorithms showed promising results on different dynamic optimization problems (DOPs). The principle of integrating immigrants schemes within ACO is to introduce newly generated ants that will replace other ants in the current population. One of the most advanced immigrants schemes is the elitism-based immigrants scheme, where the best ant from the previous environment is used as the base to generate immigrants. So far, the replacement rate used for elitism-based immigrants in ACO remained fixed during the execution of the algorithm. In this paper the impact of the replacement rate on the performance of ACO algorithms with elitism-based immigrants is examined. In addition, an adaptive replacement rate is proposed and compared with fixed and optimized replacement rates based on a series of DOPs. The experiments show that the adaptive scheme provides an automatic way to set a good value, although not the optimal one, for the replacement rate within ACO with elitism-based immigrants for DOPs.

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

Ant colony optimization, immigrants schemes, dynamic optimization problems

Citation

Mavrovouniotis, M. and Yang, S. (2014) Elitism-based immigrants for ant colony optimization in dynamic environments: Adapting the replacement rate. Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China, July 2014, pp. 1752-1759.

Rights

Research Institute