University of Surrey

Test tubes in the lab Research in the ATI Dance Research

On evolutionary optimization of large problems using small populations

Jin, Y, Olhofer, M and Sendhoff, B (2005) On evolutionary optimization of large problems using small populations

[img] PDF
36111140.pdf
Restricted to Repository staff only
Available under License : See the attached licence file.

Download (191kB)
[img] PDF (licence)
SRI_deposit_agreement.pdf
Restricted to Repository staff only

Download (33kB)

Abstract

Small populations are very desirable for reducing the required computational resources in evolutionary optimization of complex real-world problems. Unfortunately, the search performance of small populations often reduces dramatically in a large search space. To addresses this problem, a method to find an optimal search dimension for small populations is suggested in this paper. The basic idea is that the evolutionary algorithm starts with a small search dimension and then the search dimension is increased during the optimization. The search dimension will continue to increase if an increase in the search dimension improves the search performance. Otherwise, the search dimension will be decreased and then kept constant. Through empirical studies on a test problem with an infinite search dimension, we show that the proposed algorithm is able to find the search dimension that is the most efficient for the given population size. © Springer-Verlag Berlin Heidelberg 2005.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
AuthorsEmailORCID
Jin, YUNSPECIFIEDUNSPECIFIED
Olhofer, MUNSPECIFIEDUNSPECIFIED
Sendhoff, BUNSPECIFIEDUNSPECIFIED
Date : 2005
Identification Number : https://doi.org/10.1007/11539117_154
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 14:42
Last Modified : 28 Mar 2017 14:42
URI: http://epubs.surrey.ac.uk/id/eprint/532839

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800