Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5975
Title: Memory based on abstraction for dynamic fitness functions
Authors: Richter, H
Yang, S
Keywords: Evolutionary Algorithms;Dynamic optimization problems
Issue Date: 2008
Publisher: Springer
Citation: EvoWorkshops 2008: Applications of Evolutionary Computing, Lecture Notes in Computer Science 4974: 597 - 606, 2008
Abstract: This paper proposes a memory scheme based on abstraction for evolutionary algorithms to address dynamic optimization problems. In this memory scheme, the memory does not store good solutions as themselves but as their abstraction, i.e., their approximate location in the search space. When the environment changes, the stored abstraction information is extracted to generate new individuals into the population. Experiments are carried out to validate the abstraction based memory scheme. The results show the efficiency of the abstraction based memory scheme for evolutionary algorithms in dynamic environments.
Description: Copyright @ Springer-Verlag Berlin Heidelberg 2008.
URI: http://www.springerlink.com/content/941886547j48245j/
http://bura.brunel.ac.uk/handle/2438/5975
DOI: http://dx.doi.org/10.1007/978-3-540-78761-7_65
ISSN: 0302-9743
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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