Please use this identifier to cite or link to this item:
Title: Explicit memory schemes for evolutionary algorithms in dynamic environments
Authors: Yang, S
Issue Date: 2007
Publisher: Springer-Verlag
Citation: Evolutionary Computation in Dynamic and Uncertain Environments, Yang, S; Ong, Y; Jin, Y (Ed(s)), Chapter 1 (vol 51) : 3 - 28, Mar 2007
Abstract: Problem optimization in dynamic environments has atrracted a growing interest from the evolutionary computation community in reccent years due to its importance in real world optimization problems. Several approaches have been developed to enhance the performance of evolutionary algorithms for dynamic optimization problems, of which the memory scheme is a major one. This chapter investigates the application of explicit memory schemes for evolutionary algorithms in dynamic environments. Two kinds of explicit memory schemes: direct memory and associative memory, are studied within two classes of evolutionary algorithms: genetic algorithms and univariate marginal distribution algorithms for dynamic optimization problems. Based on a series of systematically constructed dynamic test environments, experiments are carried out to investigate these explicit memory schemes and the performance of direct and associative memory schemes are campared and analysed. The experimental results show the efficiency of the memory schemes for evolutionary algorithms in dynamic environments, especially when the environment changes cyclically. The experimental results also indicate that the effect of the memory schemes depends not only on the dynamic problems and dynamic environments but also on the evolutionary algorithm used.
Description: Copyright @ 2007 Springer-Verlag
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext.pdf327.14 kBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.