Pre-scheduled colony size variation in dynamic environments

Date

2017-04-19

Advisors

Journal Title

Journal ISSN

ISSN

DOI

Volume Title

Publisher

Springer

Type

Conference

Peer reviewed

Yes

Abstract

The performance of the MAX -MIN ant system (MMAS) in dynamic optimization problems (DOPs) is sensitive to the colony size. In particular, a large colony size may waste computational resources whereas a small colony size may restrict the searching capabilities of the algorithm. There is a trade off in the behaviour of the algorithm between the early and later stages of the optimization process. A smaller colony size leads to better performance on shorter runs whereas a larger colony size leads to better performance on longer runs. In this paper, pre-scheduling of varying the colony size of MMAS is investigated in dynamic environments.

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

Citation

Mavrovouniotis, M., Ioannou, A. and Yang, S. (2017) Pre-scheduled colony size variation in dynamic environments. EvoApplications 2017: Applications of Evolutionary Computation, 2017.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)