Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5845
Title: Continuous dynamic problem generators for evolutionary algorithms
Authors: Tinos, R
Yang, S
Keywords: Dynamic programming;Genetic algorithms;Search problems
Issue Date: 2007
Publisher: IEEE
Citation: IEEE Congress on Evolutionary Computation (CEC 2007), Singapore: 236 - 243, 25-28 Sep 2007
Abstract: Addressing dynamic optimization problems has attracted a growing interest from the evolutionary algorithm community in recent years due to its importance in the applications of evolutionary algorithms in real world problems. In order to study evolutionary algorithms in dynamic environments, one important work is to develop benchmark dynamic environments. This paper proposes two continuous dynamic problem generators. Both generators use linear transformation to move individuals, which preserves the distance among individuals. In the first generator, the linear transformation of individuals is equivalent to change the direction of some axes of the search space while in the second one it is obtained by successive rotations in different planes. Preliminary experiments were carried out to study the performance of some standard genetic algorithms in continuous dynamic environments created by the proposed generators.
Description: This article is posted here with permission from IEEE - Copyright @ 2007 IEEE
URI: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4424477&tag=1
http://bura.brunel.ac.uk/handle/2438/5845
DOI: http://dx.doi.org/10.1109/CEC.2007.4424477
ISBN: 978-1-4244-1339-3
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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