University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Evolutionary Complex Engineering Optimization: Opportunities and Challenges

Chai, T, Jin, Y and Sendhoff, B (2013) Evolutionary Complex Engineering Optimization: Opportunities and Challenges IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 8 (3). pp. 12-15.

Full text not available from this repository.
Item Type: Article
Authors :
NameEmailORCID
Chai, TUNSPECIFIEDUNSPECIFIED
Jin, Yyaochu.jin@surrey.ac.ukUNSPECIFIED
Sendhoff, BUNSPECIFIEDUNSPECIFIED
Date : 1 August 2013
Identification Number : https://doi.org/10.1109/MCI.2013.2264563
Uncontrolled Keywords : Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, OPERATION
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:55
Last Modified : 17 May 2017 15:06
URI: http://epubs.surrey.ac.uk/id/eprint/837234

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