Associative memory scheme for genetic algorithms in dynamic environments

Date

2006

Advisors

Journal Title

Journal ISSN

ISSN

DOI

Volume Title

Publisher

Springer

Type

Conference

Peer reviewed

Yes

Abstract

In recent years dynamic optimization problems have attracted a growing interest from the community of genetic algorithms with several approaches developed to address these problems, of which the memory scheme is a major one. In this paper an associative memory scheme is proposed for genetic algorithms to enhance their performance in dynamic environments. In this memory scheme, the environmental information is also stored and associated with current best individual of the population in the memory. When the environment changes the stored environmental information that is associated with the best re-evaluated memory solution is extracted to create new individuals into the population. Based on a series of systematically constructed dynamic test environments, experiments are carried out to validate the proposed associative memory scheme. The environmental results show the efficiency of the associative memory scheme for genetic algorithms in dynamic environments.

Description

Keywords

Associative memory scheme, Genetic algorithm, Dynamic environments

Citation

Yang, S. (2006) Associative memory scheme for genetic algorithms in dynamic environments. EvoWorkshops 2006: Applications of Evolutionary Computing, Lecture Notes in Computer Science, 3907, pp. 788-799

Rights

Research Institute

Institute of Artificial Intelligence (IAI)