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http://bura.brunel.ac.uk/handle/2438/5820
Title: | Learning behavior in abstract memory schemes for dynamic optimization problems |
Authors: | Richter, H Yang, S |
Keywords: | Evolutionary algorithm;Dynamic optimization problem;Learning;Memory dynamics |
Issue Date: | 2009 |
Publisher: | Springer Verlag |
Citation: | Soft Computing, 13(12): 1163 - 1173, Oct 2009 |
Abstract: | Integrating memory into evolutionary algorithms is one major approach to enhance their performance in dynamic environments. An abstract memory scheme has been recently developed for evolutionary algorithms in dynamic environments, where the abstraction of good solutions is stored in the memory instead of good solutions themselves to improve future problem solving. This paper further investigates this abstract memory with a focus on understanding the relationship between learning and memory, which is an important but poorly studied issue for evolutionary algorithms in dynamic environments. The experimental study shows that the abstract memory scheme enables learning processes and hence efficiently improves the performance of evolutionary algorithms in dynamic environments. |
Description: | This is the post-print version of this article. The official article can be accessed from the link below - Copyright @ 2009 Springer Verlag |
URI: | http://bura.brunel.ac.uk/handle/2438/5820 |
DOI: | http://dx.doi.org/10.1007/s00500-009-0420-6 |
ISSN: | 1432-7643 |
Appears in Collections: | Publications Computer Science Dept of Computer Science Research Papers |
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